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Site Analysis Categories You Need to Cover For Your Architecture Thesis Project

Neha Sharma

05 mins read

After having spent hours brainstorming ideas, building the perfect brief and selecting a great site for your architecture thesis topic, the question that pops into every student's mind is, where do I start?

While you build a brief and an area program, you need to simultaneously be conducting a detailed site analysis. Being architecture students, we’re no strangers to a good site analysis, but sometimes it’s good to have a checklist to see what all you should be covering!

Architecture Site Analysis

As we know, the Site Analysis is a study of the portion of land selected for your thesis project. It’s a crucial step involving the collection of data on all possible tangible and intangible aspects of your site, to help you make informed design decisions throughout the semester.

For all categories we will put down as a part of the checklist, the process of a good site analysis could be broken down into the following three parts: Documentation: Gathering all relevant data. Analysis: Critically studying the gathered data. Inferences: Making possible deductions from the analysis for your design.

The three steps of a Site Analysis (Source: Author)

Agreed that it is a formidable task, but do not be overwhelmed. Read through our checklist of site analysis categories for your architecture thesis project, and make one for yourself!

[Read: 7 Tips on Choosing the Perfect Architecture Thesis Topic For You ]

1. Movement, Connectivity and Circulation

The suitability of your site for the chosen architecture thesis topic is determined by the connections it has to the surroundings. The connectivity of your site can be on 2 scales: Macro and Micro.

Macro-connectivity is on a larger scale which explores access routes to the major nodes in a region like transit terminals, hospitals, offices, commercial centres, etc.

Micro-connectivity is defined by the immediate site network like access roads, surrounding buildings and proximity to project relevant utilities. This may help plan the major circulation paths on site.

Knowing how well-connected (or not) your site is will help make crucial design decisions like entrances and exits, how much parking you need, what kind of traffic you’re catering to, etc.

Source: www.aucklanddesignmanual.co.nz

2. Immediate Site Context

Context is what is happening (or has happened) in, out, around and about the site! It involves areas like the local architectural style, materials, construction techniques, historical and cultural background, analysis of edge conditions , urban morphology , prior uses, political conditions or anything that may be relevant to the site.

I don’t think we need to explain why this is important to your thesis, because if you needed to know, you wouldn’t have reached thus far in architecture school!

Source: www.pinterest.com

3. Zoning and Development Control Regulations

Every region has laid down its development control regulations, zoning and land use patterns. Various factors like site location, type of zone it falls under, land use as per DCR, prevailing vehicular/ pedestrian traffic (high, medium, low-density zones) and permissible setbacks give you an idea of how suitable the site is for the project chosen. Prominent points to note would be the FAR , permissible built-up area, setbacks, height-restrictions, etc.

This will make your thesis as realistic as possible, giving you guidelines within which you must plan and would prevent any faculty or jury member from questioning the legitimacy of your thesis.

Source: Studio 6 site analysis, slideshare.com

4. Climate and Ecology

What is good architecture if not an immediate response to climate? One of the first and most important things to know about your site is its climatic conditions. To make things simple, divide the study into 2 parts:

Macro-climate - The climate of the larger chunk of land, like the region or country the site is located in and remains constant (more or less) irrespective of the architectural developments taking place. Here, the sun path, seasonal temperatures, humidity, annual precipitation and prevailing wind direction are common data acquisition sections and are the deciding factors for (but not limited to) the building’s location on site, its orientation, form and massing.

Micro-climate - The local climate conditions that might affect design decisions like the presence of water-bodies nearby, existing vegetation, topography, etcetera. It is especially crucial when dealing with projects abutting lakes, rivers or the sea, where the effect of water-body may dictate your design development. Or a site in a hilly region where contour study/slope analysis is a must!

Source: www.lassetercoa.wordpress.com

5. Demographics

Design is for your users, and good architecture takes full account of them. Demographic analysis involves the socio-economic study of a region by categorising its population into religion, ethnicity, cultural background, income profiles, nativity and occupation. This analysis is key for socially or culturally sensitive architecture thesis topics like places of worship, community housing and welfare centres.

Want to create something for the people? Know them first!

6. Services and Amenities

A brief study of site services is essential to know how your site is connected to basic amenities like drinking water, electricity, drainage, sewerage, or telephone and internet lines (all hail WiFi!).

For planning and locating your building services, you need to know where the service lines are going and how they’re laid out, including any existing service features on site.

7. Sensory Analysis

Does your site have points where the view is just fantastic (maybe overlooking a waterbody, eye-soothing greenery or the cityscape)? Or maybe it has spots where there is unbearable noise (could be from your weekly vegetable market or that one lane through which the whole city has to travel)!

More often than not, such sensory analysis of the site is neglected. But when such observations are noted and inferred from, they can be some of the strongest drivers of your architecture thesis project.

Source: www.wp.com

It is always good to make a checklist while dealing with a lot of data, and the site analysis is no exception. However, please do not limit yourself to the above list, as each site is unique and may have exceptional needs. You may need to do additional analysis particular to the features of your thesis, as it reflects the individuality of both the project and the student. Depending on your architecture thesis topic, other categories may include historical analysis, water/soil integrity sampling, traffic volume analysis, and more.

Having read the above list that has been put in place for you, go ahead and put your hard work and magic in place too! Novatr is always here to help.

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How To Write an Architecture Dissertation

• Updated: April 9, 2024

Embarking on the journey of writing an architecture dissertation marks a pivotal moment in the academic life of an architecture student.

This rigorous exercise is not merely about showcasing design prowess; it’s an intricate blend of research, analysis, and the eloquent presentation of ideas and findings.

The dissertation serves as a testament to the knowledge and skills honed over years of study , and more importantly, it reflects a student’s ability to contribute thoughtfully to the architectural discourse.

The process of crafting an architecture dissertation can be as daunting as it is exciting. It involves delving into uncharted territories of design and theory, while also navigating through a sea of existing literature, case studies , and architectural precedents .

The challenge lies in identifying a unique topic that resonates with personal interests and the current architectural landscape, and then framing a research question that is both original and feasible.

This question becomes the guiding light for the entire dissertation, shaping the research, analysis, and the eventual conclusions drawn.

Here we outline a comprehensive approach to writing an architecture dissertation, inspired by a range of intriguing topics that cater to the evolving landscape of modern architecture.

From exploring the nuances of sustainable design to understanding the complexities of urban development, we will guide you through each step of this scholarly endeavor.

Whether it’s dissecting the architectural marvels of sustainable hospitals or innovating designs for public spaces, the dissertation journey promises to be a deeply enriching experience, pushing the boundaries of your academic and creative capabilities.

Choosing Your Dissertation Topic

Selecting the right topic for your architecture dissertation is a crucial step that sets the foundation for your entire project.

This phase is critical in determining the direction and scope of your research, ultimately influencing the success of your dissertation.

It involves a series of steps designed to refine your interests and align them with academic and professional aspirations. Below, we delve into the methodology for choosing a compelling and relevant dissertation topic.

Identifying Your Area of Interest

The initial step in this journey is to introspect and identify what aspects of architecture ignite your passion.

Whether it’s sustainable building practices, innovative public spaces, historical restoration, or another niche, your enthusiasm for the subject will significantly influence your research and writing endeavors.

Creating a list of themes and subjects within architecture that intrigue you is a practical approach to starting this process. This list will act as a beacon, guiding you toward narrowing down your topic.

Researching Current Trends and Gaps

Keeping abreast of the latest developments in the field of architecture is essential.

This can be achieved through various means such as reading industry journals, attending webinars, or engaging with prominent architects and institutions via social media.

An effective tip is to identify gaps in the existing research or explore emerging trends that have not been extensively covered. This pursuit may uncover a distinctive and impactful dissertation topic.

Considering Practicality and Resources

It is imperative to consider the feasibility of your chosen topic, especially in terms of resource availability, data, and research material. Assessing the scope of your project and its realistic completion within the allotted timeframe is crucial.

Ensuring the accessibility of primary sources, datasets, and case studies pertinent to your topic is advisable. Should resources be limited, refining your topic may be necessary.

Consulting with Mentors and Peers

Engaging in discussions with mentors, tutors, or peers about your ideas can provide invaluable insights. They may suggest resources, offer advice, and assist in refining your topic.

Remaining open to feedback and considering different perspectives can often illuminate your topic in a new light, offering fresh angles and ideas.

Aligning with Your Career Aspirations

Choosing a dissertation topic that complements your future career goals or specialization areas is beneficial. This approach transforms your dissertation from a mere academic requirement into a valuable asset for your professional journey.

Reflect on how your dissertation can enhance your portfolio and improve your employability within your chosen architecture field.

Exploring Case Studies and Examples

Seeking inspiration from relevant case studies can be incredibly helpful. Analyzing successful projects that align with your interests can aid in defining both your topic and research approach.

For instance, if sustainable architecture fascinates you, exploring projects like the Edge in Amsterdam or the Pixel Building in Melbourne might provide the inspiration needed to solidify your topic.

Narrowing Down and Focusing

With a general area of interest in mind, the next step is to hone in on a specific aspect. Focusing your topic allows for a deeper investigation and the development of a robust dissertation.

For example, if urban architecture captures your interest, you might narrow your focus to topics such as the revitalization of historic urban districts or the integration of green spaces in city centers.

Finalizing and Validating Your Choice

After narrowing down your topic, it’s important to validate its relevance and originality. Confirm that it contributes value to the field and isn’t overly saturated in existing literature.

Conducting a preliminary literature review can provide insights into how much has been written about your topic and assist in formulating your research question.

Choosing your dissertation topic is a reflective and meticulous process, requiring exploration and refinement. It’s crucial to select a subject that not only contributes to the field of architecture but also resonates with your personal and professional ambitions.

Through thoughtful consideration and comprehensive research, you can select a topic that lays the groundwork for a successful dissertation.

Formulating Your Research Question

Understanding the field and identifying the gap.

The process begins by deeply engaging with the current research landscape of your chosen topic.

This foundational step entails a thorough review of existing literature, a grasp of the ongoing debates within the field, and a keen eye for areas that remain lightly explored or entirely untouched.

The primary aim here is to carve out a unique niche for your study, one that promises fresh insights or presents a challenge to established theories.

This niche might manifest as an under-researched dimension, a novel perspective on a familiar subject, or an innovative methodology addressing a known issue.

Refining Your Topic from Broad to Specific

Once the broader landscape is understood, the journey narrows down to specifying your research interest.

This phase is crucial for transitioning from a general area, such as urban architecture, to a more defined subject, such as the influence of urban design on community well-being.

Additionally, it’s essential to conduct a feasibility check to ensure the chosen topic is practical in terms of scope, time, resources, and data availability.

The ideal topic should strike a balance between complexity and manageability, ensuring it is both intriguing and achievable.

Crafting the Research Question with Clarity and Focus

The core of your research endeavor is the formulation of a clear, focused, and concise research question. This question acts as a beacon, guiding your research direction and shaping the data collection process.

For instance, in the realm of sustainable architecture, a potent question might be, “How does the employment of recycled materials in construction diminish the ecological footprint of urban development?”

This question not only specifies the research’s direction but also underlines its relevance and purpose.

Aligning the Research Question with Objectives

The research question should resonate with the broader objectives of your study, whether it aims to propose new solutions, analyze current issues, or explore conceptual theories.

For example, if the goal is to suggest practical solutions, a fitting question could be, “What are the most effective strategies for integrating green spaces into urban high-density housing?”

This alignment ensures that the research remains purpose-driven and focused on achieving its stated aims.

Hypothesis Formation through Predictive Statements

Based on the initial exploration, you are expected to formulate a hypothesis or a predictive statement that your research will test.

For example, a hypothesis in sustainable architecture might posit that “Utilizing biodegradable materials in residential construction significantly curtails the carbon footprint.”

This hypothesis sets the stage for empirical investigation and analysis.

Incorporating Ethical Considerations into Research

It is paramount that your research upholds the highest ethical standards, particularly if it involves human participants, sensitive information, or potential environmental impacts.

For instance, research involving interviews with architects must guarantee confidentiality and informed consent to adhere to ethical research practices.

Seeking Feedback through Consultation and Peer Review

Engaging with your academic advisor or mentors is a vital step in refining your research question and ensuring its academic rigor.

Advisors can offer invaluable feedback, assisting in the honing of your question to ensure it is robust and academically sound.

Similarly, peer discussions can unveil new perspectives or identify overlooked elements, contributing to the overall strength and clarity of your research question.

The formulation of your research question marks a pivotal moment in your academic journey.

It defines the trajectory of your investigation and encapsulates your scholarly curiosity, setting the stage for a study that is not only methodologically sound but also rich in impact and significance.

Conducting Your Research

Identifying and gathering resources.

The first step in conducting comprehensive research involves assembling a wide array of resources.

This process should encompass a variety of materials including, but not limited to, academic journals, architectural books, reputable online databases, case studies, and interviews with professionals.

For example, when investigating sustainable architecture, it’s advisable to include journals focused on environmental design, books detailing sustainable materials, and case studies highlighting green buildings.

Additionally, leveraging digital libraries and archives can prove invaluable, offering access to thesis papers, design portfolios, and scholarly articles that provide both historical and contemporary insights.

Fieldwork and Case Studies

Engaging in fieldwork by visiting relevant architectural sites allows for the observation of design principles, materials, and environmental integration of buildings.

These visits can unearth practical insights, particularly in areas such as sustainable design practices highlighted by recent eco-friendly construction projects.

Furthermore, interviewing architects, designers, and scholars can unveil unique perspectives and knowledge not found in published sources. It’s crucial to approach these interviews with well-prepared questions that align with your research objectives.

Data Collection and Analysis

Research typically involves the gathering of both quantitative data, like energy efficiency ratings, and qualitative data, such as personal opinions on design aesthetics.

Employing suitable analysis methods for each type of data is essential, with statistical analysis for quantitative data and thematic analysis for qualitative data.

It’s equally important to critically assess each source’s reliability, relevance, and potential bias, ensuring the credibility of the information used in your research.

Organizing and Documenting Your Research

Developing effective note-taking and organizational strategies is crucial for managing the vast amounts of information collected during research.

This may involve utilizing digital tools for reference management or maintaining a simple, yet organized, spreadsheet.

Additionally, keeping a detailed research log of activities, including dates, contacts made, and interviews conducted, will not only aid in organization but also support the methodology section of your dissertation.

Ethical Considerations

Respecting copyright and intellectual property rights is paramount, requiring proper citation of all sources in accordance with institutional guidelines.

When conducting interviews or surveys, it’s imperative to obtain consent from participants, ensuring transparency in the use of gathered information while maintaining the confidentiality and anonymity of your sources.

Embarking on research is a complex and nuanced endeavor that necessitates a thoughtful approach to source diversity, fieldwork participation, and data organization.

Adhering to ethical standards throughout the process is essential. The thoroughness and integrity of your research will significantly influence the depth and impact of your dissertation, thereby contributing to the broader field of architecture.

Writing your Dissertation

This is where you translate your research and ideas into a coherent, well-structured document. This section of the process requires meticulous planning, clear articulation, and a consistent academic style. Here are the key steps to follow:

1. Developing a Structured Outline:

• Example: Introduce the concept of sustainable architecture, highlighting its importance and relevance in today’s world.
• Example: Review studies on the use of recycled materials in architecture, focusing on their application in hospital buildings.
• Example: Detail your approach to collecting data on sustainable hospital designs, including any site visits, interviews, or architectural analyses conducted.
• Example: Showcase the results from your case studies or interviews, providing specific examples of successful sustainable practices in hospital design.
• Example: Discuss how the use of recycled materials in hospitals impacts environmental sustainability and patient well-being.
• Example: Emphasize the importance of sustainable materials in architecture and propose future research directions, such as long-term sustainability studies.

2. Writing with Clarity and Cohesion:

• Example: Use technical and architectural terms appropriately and explain any complex concepts for clarity.
• Example: Link the discussion on sustainable materials to broader sustainability goals in architecture, leading smoothly into your conclusion.
• Example: If your university requires APA formatting, ensure all your citations and references are formatted accordingly.

3. Incorporating Visual Elements:

• Example: Include a diagram illustrating the lifecycle of recycled materials in hospital construction.
• Example: Refer to each figure in the text and explain its relevance to your discussion.

4. Revision and Feedback:

• Example: Have a fellow architecture student review your methodology section for clarity and comprehensiveness.
• Example: Check for consistency in terminology, especially architectural terms, and ensure all figures are correctly numbered.

Presenting Your Findings

Once you have conducted your research and gathered all necessary data, a crucial step is presenting your findings effectively. This section is where you demonstrate how your research contributes to the field of architecture, applying your skills in both analysis and presentation.

Organizing Your Data

To start, ensure your findings are arranged in a clear and logical order, whether it be chronological, thematic, or directly tied to your research questions.

For instance, in a dissertation examining sustainable materials in hospital design, it would be prudent to categorize your findings by types of materials, their applications, and their overall impact on the environment.

Visual Presentation

Given that architecture heavily relies on visual comprehension, your dissertation should be enriched with diagrams, charts, photographs, and sketches.

These visual aids are meant to enhance and clarify your narrative, not serve as a substitute for it. For example, incorporating architectural sketches that show the application of sustainable materials in various hospital areas can significantly aid in understanding.

Critical Analysis

Beyond presenting data, it’s crucial to interpret your findings. Discuss the significance of your results within the context of your research question and the broader architectural field.

A detailed analysis of how a specific sustainable material contributes to a hospital’s environmental performance exemplifies this approach well.

Balanced Discussion

Recognizing the strengths and weaknesses of your findings demonstrates a comprehensive understanding and critical thinking ability.

For example, while highlighting the advantages of using recycled materials in hospitals, also consider their potential drawbacks, such as issues with durability or availability.

Linking Theory and Practice

Connect your empirical findings back to the theoretical framework laid out in your literature review. This could involve linking practical observations about sustainable materials to established theories of environmental sustainability.

Use of Case Studies

Incorporating case studies provides tangible evidence to support your findings. Citing a particular hospital project that effectively utilized recycled materials in its construction can offer valuable real-world insights.

Narrative Flow

Crafting your findings into a compelling narrative can make your dissertation more engaging and memorable. For instance, narrating how material selection impacts hospital design and patient experience can make for a persuasive argument.

Recommendations and Implications

Base your practical recommendations on your findings and discuss how these can be implemented in architectural practice. Proposing guidelines for selecting sustainable materials in future hospital projects is a practical example of this.

Reflecting on Research Questions

Ensure that your presentation directly addresses the research questions or objectives outlined at the beginning of your dissertation. Revisiting your initial query on the role of sustainable materials in enhancing hospital architecture and demonstrating how your findings offer insights is crucial.

Engaging Presentation Style

The style of your presentation is just as important as its content. Utilize clear, concise language and ensure that your visual aids are of high quality and relevant to your discussion.

Effective visual aids that are easily understandable and directly related to your findings can significantly enhance your presentation.

By meticulously organizing your data, critically analyzing your findings, and engagingly presenting your research, you can craft a compelling and coherent argument.

This approach not only highlights the significance of your research within the architectural field but also bridges the gap between theory and practice, making for a strong, persuasive dissertation.

To Sum Up…

As you reach the conclusion of your architecture dissertation journey, it’s essential to reflect on the journey you’ve embarked upon. This process is not just about fulfilling an academic requirement; it’s about contributing to the ever-evolving field of architecture.

Your dissertation is a testament to your growth as a scholar and a professional, showcasing your ability to conduct in-depth research, analyze complex topics, and present your findings with clarity and insight.

Key Takeaways and Impact

Your dissertation should leave a lasting impression on its readers. It’s vital to recapitulate your main findings and underscore their significance in the context of architecture.

For instance, if your dissertation focused on sustainable materials in hospital construction, highlight how your research provides new insights or solutions that could be applied in real-world scenarios.

Emphasize how your findings can influence future architectural designs, sustainability practices, or policy-making.

Reflecting on Challenges and Learnings

Acknowledge the challenges you faced and how they shaped your research process. Reflecting on these hurdles not only humanizes your journey but also provides valuable insights for future researchers who may tread a similar path.

Discuss the limitations of your study candidly, as recognizing these constraints is a hallmark of rigorous academic research.

Future Directions

Propose avenues for future research, building on your work. This could involve exploring new materials, different architectural styles, or other geographical contexts.

By suggesting future research directions, you’re contributing to a continuous dialogue in your field and potentially inspiring others to build upon your work.

Personal Growth and Future Aspirations

Finally, consider how this process has contributed to your personal and professional development. Discuss your aspirations in the field of architecture and how your dissertation has equipped you with the skills and knowledge to pursue these goals.

Whether it’s advancing sustainable practices, influencing urban design, or innovating in residential construction, your journey doesn’t end here. Your dissertation is a stepping stone to further explorations and achievements in the dynamic and impactful world of architecture.

In conclusion, your architecture dissertation is more than just a document; it’s a manifestation of your dedication, intellect, and passion for architecture. It not only contributes to your field but also sets the foundation for your future endeavors in this exciting and vital discipline.

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20 Types of Architecture thesis topics

An architectural thesis is perhaps the most confusing for a student because of the range of typologies of buildings that exist. It also seems intimidating to pick your site program and do all the groundwork on your own. While choosing an architectural thesis topic, it is best to pick something that aligns with your passion and interest as well as one that is feasible. Out of the large range of options, here are 20 architectural thesis topics .

1. Slum Redevelopment (Urban architecture)

Slums are one of the rising problems in cities where overcrowding is pertinent. To account for this problem would be one of great value to the city as well as the inhabitants of the slum. It provides them with better sanitation and well-being and satisfies their needs.

2. Maggie Center (Healthcare architecture)

This particular typology of buildings was coined by a cancer patient,  Margaret Keswick Jencks,   who believed that cancer-treatment centres’ environment could largely improve their health and wellbeing by better design. This led a large number of starchitects to participate and build renowned maggie centres.

3. Urban Sprawl Redesign (Urban design)

The widening of city boundaries to accommodate migrants and overcrowding of cities is very common as of late. To design for the constant urban sprawl would make the city life more convenient and efficient for all its users.

4. Redesigning Spaces Under Elevated Roads and Metros (Urban infrastructure)

A lot of space tends to become dead space under metros or elevated roads. To use these spaces more efficiently and engage them with the public would make it an exciting thesis topic.

5. Urban Parks (Urban landscape)

Urban parks are not only green hubs for the city, which promotes the well-being of the city on a larger level, but they also act as great places for the congregation and bring a community together.

6. Reusing Abandoned Buildings (Adaptive reuse)

All buildings after a point become outdated and old but, what about the current old and abandoned buildings? The best way to respond to these is not by demolishing them; given the amount of effort it takes to do so, but to enhance them by restoring and changing the building to current times.

7. Farming in Cities (Green urban spaces)

With climate change and population on the rise, there is statistical proof that one needs to start providing farming in cities as there is not sufficient fertile land to provide for all. Therefore, this makes a great thesis topic for students to explore.

8. Jails (Civil architecture)

To humanize the function of jails, to make it a place of change and rehabilitation, and break from the stereotypical way of looking at jails. A space that will help society look at prisoners as more than monsters that harm, and as fellow humans that are there to change for everyone’s betterment.

9. Police Academies (Civil architecture)

Academies that train people to be authoritative and protective require spaces for training mentally and physically; focussing on the complexity of the academy and focussing on the user to enhance their experience would work in everyone’s favour.

10. High Court (Civil architecture)

Courtrooms are more often than not looked at as spaces that people fear, given the longevity of court cases. It can be a strenuous space; therefore, understanding the user groups’ state of mind and the problems faced can be solved using good design. 

11. Disaster-resilient structures (Disaster-relief architecture)

Natural disasters are inevitable. Disaster-resilient structures are build suitably for the natural disasters of the region while also incorporating design into it, keeping in mind the climatic nature of the location.

12. Biophilic design (Nature-inspired architecture)

As humans, we have an innate love for nature, and the struggle between integrating nature and architecture is what biophilic design aims towards. To pick a topic where one would see minimal use of natural elements and incorporate biophilic design with it would be very beneficial.

13. Metro stations and Bus terminals (Transportation spaces)

Bus terminals and metro stations are highly functional spaces that often get crowded; and to account for the crowd and the problems that come with it, plus elevate the experience of waiting or moving, would contribute to making it a good thesis topic.

14. Airport design (Transportation spaces)

Airport designing is not very uncommon; however, it is a rather complex program to crack; thereby, choosing this topic provides you with the opportunity to make this space hassle-free and work out the most efficient way to make this conducive for all types of users.

15. Sports Complex (Community architecture)

If your passion lies in sports, this is a go-to option. Each sport is played differently, different materials are used, and the nature of the sport and its audience is rather complicated. However, to combine this and make it a cohesive environment for all kinds of users would make a good thesis topic.

16. Stadium (Community architecture)

Unlike a sports complex, one could also pick one sport and look at the finer details, create the setting, and experience for it; by designing it to curate a nice experience for the players, the public, and the management.

17. Waste-recycling center (Waste management)

Reducing waste is one of the most fundamental things we must do as humans. Spaces where recycling happens must be designed consciously. Just like any other space, it has been given importance over the years, and this would make a good thesis topic to provide the community with.

18. Crematorium (Public architecture)

Cremation of a loved one or anyone for that matter is always a rather painful process and a range of emotions is involved when it comes to this place. Keeping in mind the different types of people and emotions and making your thesis about this would mean to enhance this experience while still keeping the solemnity of it intact.

19. Museums (Community architecture)

Museums are spaces of learning, and the world has so much to offer that one could always come up with different typologies of museums and design according to the topic of one’s interest. Some of the examples would be cultural heritage, modern art, museum of senses, and many more.

20. Interpretation center (Community architecture)

An interpretation center is a type of museum located near a site of historical, cultural, or natural relevance that provides information about the place of interest through various mediums.

References:

• 2022. 68 Thesis topics in 5 minutes . [image] Available at: <https://www.youtube.com/watch?v=NczdOK7oe98&ab_channel=BlessedArch> [Accessed 1 March 2022].
• Bdcnetwork.com. 2022. Biophilic design: What is it? Why it matters? And how do we use it? | Building Design + Construction . [online] Available at: <https://www.bdcnetwork.com/blog/biophilic-design-what-it-why-it-matters-and-how-do-we-use-it> [Accessed 1 March 2022].
• RTF | Rethinking The Future. 2022. 20 Thesis topics related to Sustainable Architecture – RTF | Rethinking The Future . [online] Available at: <https://www.re-thinkingthefuture.com/rtf-fresh-perspectives/a1348-20-thesis-topics-related-to-sustainable-architecture/> [Accessed 1 March 2022].
• Wdassociation.org. 2022. A List Of Impressive Thesis Topic Ideas In Architecture . [online] Available at: <https://www.wdassociation.org/a-list-of-impressive-thesis-topic-ideas-in-architecture.aspx> [Accessed 1 March 2022].

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Flora is a student of architecture, with a passion for psychology and philosophy. She loves merging her interests and drawing parallels to solve and understand design problems. As someone that values growth, she uses writing as a medium to share her learning and perspective.

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Selected Architecture Thesis Projects: Fall 2020

Clockwise from top left: “Citing the Native Genius” by Taylor Cook, “Pair of Dice, Para-Dice, Paradise: A Counter-Memorial to Victims of Police Brutality” by Calvin Boyd, “The Magic Carpet” by Goli Jalali, “Stacked Daydreams: Ceiling-Scape for the Neglected” by Zai Xi Jeffrey Wong, and “Up from the Past: Housing as Reparations on Chicago’s South Side” by Isabel Strauss

Five films showcase a selection of Fall 2020 thesis projects from the Department of Architecture.

Pair of Dice, Para-Dice, Paradise: A Counter-Memorial to Victims of Police Brutality

This thesis is a proposal for a counter-memorial to victims of police brutality. The counter-memorial addresses scale by being both local and national, addresses materiality by privileging black aesthetics over politeness, addresses presence/absence by being more transient than permanent, and lastly, addresses site by being collective rather than singular. The result is an architecture that plays itself out over 18,000 police stations across America and the Washington Monument at the National Mall, two sites that are intrinsically linked through the architecture itself: negative “voids” at police stations whose positive counterparts aggregate at the Mall.

The critical question here is whether or not the system in which police brutality takes place can be reformed from within, or if people of color need to seek their utopia outside of these too-ironclad structures. This counter-memorial, when understood as an instrument of accountability (and therefore a real-time beacon that measures America’s capacity to either change or otherwise repeat the same violent patterns), ultimately provides us with an eventual answer.

Author: Calvin Boyd, MArch I 2020 Advisor: Jon Lott , Assistant Professor of Architecture Duration: 11 min, 2 sec

Thesis Helpers: Shaina Yang (MArch I 2021), Rachel Coulomb (MArch I 2022)

The Magic Carpet

The Persian Carpet and the Persian Miniature painting have served as representation tools for the Persian Gar­den and the idea of paradise in Persian culture since antiquity. The word paradise derives from the Persian word pari-daeza meaning “walled enclosure.” The garden is always walled and stands in opposition to its landscape. This thesis investigates the idea of a contemporary image of paradise in the Iranian imagination by using carpets and miniature paintings as a tool for designing architecture. The garden, with its profound associations, provided a world of metaphor for the classical mystic poets. One of the manuscripts describing the Persian garden is called Haft Paykar – known as the Seven Domes – written by the 12th century Persian poet called Nizami. These types of manuscripts were made for Persian kings and contain within them miniature paintings and poetry describing battles, romances, tragedies, and triumphs that compromise Iran’s mythical and pre-Islamic history. The carpet is the repeating object in the minia­ture paintings of the manuscript. This thesis deconstructs the carpet in seven ways in order to digitally reconstruct the miniature paintings of the Seven Domes and the image of paradise with new techniques.

Author: Goli Jalali, MArch I 2021 Advisor: Jennifer Bonner , Associate Professor of Architecture Duration: 8min, 28 sec

Up from the Past: Housing as Reparations on Chicago’s South Side

Do people know what the Illinois Institute of Technology and the South Side Planning Board and the city of Chicago and the state of Illinois and the United States government did to the Black Metropolis? If they know, do they care? Is it too hard to hold these entities accountable? If we held them accountable, could we find justice for those that were displaced? What would justice look like? What comes after Mecca? What types of spaces come after Mecca? Are they different than what was there before? Are they already there? What defines them? Can Reparations be housing? How many people are already doing this work? How many people are doing this work in academia? On the ground? Is the word “Reparations” dead? What do we draw from? Who is this for? Do white men own the legacy of the architecture that defined the Black Metropolis? How personal should this work be? How anecdotal? How quantitative? Does the design need to be inherently spatial? Or atmospheric? What should it feel like? How do I draw a feeling in Rhino? What are radical ways of looking? How do we reclaim racialized architecture? Do we? Should we even talk about these things?

Author: Isabel Strauss, MArch I 2021 Advisor: Oana Stanescu , Design Critic in Architecture Duration: 4 min, 4 sec

Soundtrack Created By: Edward Davis (@DJ Eway) Production Support: Adam Maserow , Evan Orf , Glen Marquardt Collaborators: Rekha Auguste Nelson , Farnoosh Rafaie , Zena Mariem Mengesha , Edward Davis (DJ Eway) Special Thanks: Caleb Negash , Tara Oluwafemi , Maggie Janik , Ann Whiteside , Dana McKinney Guidance: Stephen Gray , John Peterson , Chris Herbert , Cecilia Conrad , Lawrence J. Vale , Ilan Strauss , Mark Lee , Iman Fayyad , Jennifer Bonner , Mindy Pugh , Peter Martinez Collage Credits: Adler and Sullivan , Bisa Butler , Carrie Mae Weems , Dawoud Bey , Deborah Roberts , Ebony G Patterson , Ellen Gallagher , Frank Lloyd Wright , Howardena Pindell , Jordan Casteel , Kerry James Marshall , Latoya Ruby Frazier , Lelaine Foster , Lorna Simpson , Mark Bradford , Mickalene Thomas , Mies van der Rohe , Nick Cave , Njideka Akunyili Crosby , Romare Bearden , Sadie Barnette More Information: architectureofreparations.cargo.site

Stacked Daydreams: Ceiling‐Scape for the Neglected

Elderly Care Adaptive Reuse of Hong Kong’s Vertical Factory

This thesis operates at the intersection of three domains of neglect:

• In the realm of building elements, the ceiling is often considered as an afterthought in the design process.
• Across building types, the vertical factory sits abandoned and anachronistic to its surroundings. It spiraled into disuse due to Hong Kong’s shifting economic focus.
• In society, the elderly are often subjected to social neglect, seen as a financial burden, and forced toward the fringes of society.

These parts experience obsolescence that led to indifference, and subsequently to boredom. I intend to draw the parallel of deterioration between the body of the elderly and the body of the vertical factory. Using a set of ceiling parts in the manner of prosthetics to reactivate the spaces into elderly care facilities, revert boredom to daydreams, and reimagine the concept of elderhood as an experimental second stage of life.

Author: Zai Xi Jeffrey Wong, MArch I AP 2021 Advisor: Eric Höweler , Associate Professor of Architecture & Architecture Thesis Coordinator Duration: 4 min, 53 sec

Citing the Native Genius

Reconstructing vernacular architecture in Hawai’i

For over 120 years, Americanization has tried to demean and erase Hawaiian language, culture, and architecture. In contemporary discourse, the vernacular architecture of Hawai’i is mostly referred to as ancient and vague. As with many Indigenous cultures, Western perspectives tend to fetishize or patronize the Hawaiian design aesthetic. Within this hierarchy of knowledge is a systemic assumption that Hawaiian vernacular architecture cannot effectively serve as a precedent resource for contemporary architects. Those who do reference the original vernacular will often classify it as utilitarian or resourceful. Regardless of intent, this narrative takes design agency away from the people involved. As a corrective, a respectful use of vernacular domestic form would benefit designers that are struggling to connect with Hawai’i’s cultural and architectural traditions.

Mining the European gaze and influence out of revivalist publications, archeological surveys and historic images reveal unique characteristics of Hawaiian domestic space. Geometric quotation and symbolic referencing are the foundational instruments in applying the discrete components, form, and organizational logic of the vernacular. The result is a design process that creates an amalgamation of decolonized form and contemporary technique. This residential project intends to revive Hawai’i’s erased domestic experience by revisiting the precolonial vernacular form and plan.

Author: Taylor Cook, MArch I 2021 Advisor: Jeffry Burchard , Assistant Professor in Practice of Architecture Duration: 5 min, 13 sec

Special Thanks: Jeffry Burchard, Cameron Wu, Kanoa Chung, Nik Butterbaugh, Carly Yong, Vernacular Pacific LLC More Information: www.vernacularhawaii.com

During the COVID-19 pandemic, the galleries in Gund Hall have been turned ‘inside out,’ with exhibitions shown through a series of exterior projections on the building’s facade. View some images from the screening of these films below:

ScholarWorks@UMass Amherst

Home > HFA > Department of Architecture > Architecture Masters Theses Collection

Architecture Masters Theses Collection

Theses from 2023 2023.

Music As a Tool For Ecstatic Space Design , Pranav Amin, Architecture

Creating Dormitories with a Sense of Home , Johnathon A. Brousseau, Architecture

The Tectonic Evaluation And Design Implementation of 3D Printing Technology in Architecture , Robert Buttrick, Architecture

Designing for the Unhoused: Finding Innovative and Transformative Solutions to Housing , Hannah C. Campbell, Architecture

Investigating Design-Functional Dimension Of Affordable Housing With Prefabrication On Dense Suburbs Of Chelsea, MA , Siddharth Jagadishbhai Dabhia, Architecture

Architecture of Extraction: Imagining New Modes of Inhabitation and Reclamation in the Mining Lifecyle , Erica DeWitt, Architecture

Utopian Thought and Architectural Design , Anthony L. Faith, Architecture

Building Hygge In-Roads into Incremental Living , Tanisha Kalra, Architecture

NATURE INSPIRED ARCHITECTURE , Salabat Khan, Architecture

Sustainable Architecture in Athletics: Using Mass Timber in an Old-Fashioned Field , Zach C. Lefever, Architecture

Off-grid Living for the Normative Society: Shifting Perception and Perspectives by Design , Patsun Lillie, Architecture

The Evolution of Chinese Supermarkets in North America: An Alternative Approach to Chinese Supermarket Design , Ruoxin Lin, Architecture

Refreshing Refinery: An Analysis of Victorian Architecture and How to Translate its Elements for Contemporary Architecture , Richard J. Marcil, Architecture

After Iconoclasm: Reassessing Monumental Practices and Redesigning Public Memorials in Twenty-First-Century Massachusetts , Lincoln T. Nemetz-Carlson, Architecture

Earthen Materials In Organic Forms: An Ecological Solution to the Urban Biosphere? , Rutuja Patil, Architecture

Adaptive (Re)purpose of Industrial Heritage Buildings in Massachusetts A Modular Strategy for Building a Community , Riya D. Premani, Architecture

Community Design: A Health Center Serving the Greater Boston Population , Brandon E. Rosario, Architecture

The Food Hub as a Social Infrastructure Framework: Restitching Communities in Boston After the Pandemic , Connor J. Tiches, Architecture

Theses from 2022 2022

Equitable Housing Generation Through Cellular Automata , Molly R. Clark, Architecture

Beneficial Invasive: A Rhizomatic Approach to Utilizing Local Bamboo for COVID Responsive Educational Spaces , Megan Futscher, Architecture

Architectural Activism Through Hip-Hop , Micaela Goodrich, Architecture

Addressing Trauma Through Architecture: Cultivating Well-being For Youth Who Have Experienced Trauma , Megan Itzkowitz, Architecture

Buildings Integrated into Landscape & Making People Care for Them: Exploring Integrated Land-Building Ecosystems and the Lifestyles Needed to Support It , Sara Mallio, Architecture

Reimagining Black Architecture , Esosa Osayamen, Architecture

Prefabricated Homes: Delivery At Your Doorsteps , Obed K. Otabil, Architecture

Memory and Resistance , Cami Quinteros, Architecture

Mycelium: The Building Blocks of Nature and the Nature of Architecture , Carly Regalado, Architecture

IN-BETWEEN SPACES: ATMOSPHERES, MOVEMENT AND NEW NARRATIVES FOR THE CITY , Paul Alexander Stoicheff, Architecture

Theses from 2021 2021

Creating New Cultural Hubs in American Cities: The Syrian Diaspora of Worcester, Massachusetts , Aleesa Asfoura, Architecture

Firesafe: Designing for Fire-Resilient Communities in the American West , Brenden Baitch, Architecture

The Beige Conundrum , Alma Crawford-Mendoza, Architecture

Cultivating Food Justice: Exploring Public Interest Design Process through a Food Security & Sustainability Hub , Madison J. DeHaven, Architecture

Physical to Virtual: A Model for Future Virtual Classroom Environments , Stephen J. Fink, Architecture

Detroit: Revitalizing Urban Communities , David N. Fite, Architecture

The Homestead Helper Handbook , Courtney A. Jurzynski, Architecture

An Architecture of a New Story , Nathan Y. Lumen, Architecture

Border Town: Preserving a 'Living' Cultural Landscape in Harlingen, Texas , Shelby Parrish, Architecture

Housing for Adults with Autism Spectrum Disorder (ASD): Creating an Integrated Living Community in Salem, MA , Tara Pearce, Architecture

From Sanctuary to Home in the Post-Interstate City , Morgan B. Sawyer, Architecture

Exploring the Use of Grid-Scale Compressed Air Energy Storage in the Urban Landscape , Connor S. Slover, Architecture

Bridging the Gaps in Public Conversation by Fostering Spaces of Activism , Karitikeya Sonker, Architecture

Re-envisioning the American Dream , Elain Tang, Architecture

Tall Timber in Denver: An Exploration of New Forms in Large Scale Timber Architecture , Andrew P. Weuling, Architecture

Theses from 2020 2020

Urban Inter-Space: Convergence of Human Interaction and Form , Clayton Beaudoin, Architecture

The Hues of Hadley Massachusetts: Pioneering Places for Preservation and Growth , Elisha M. Bettencourt, Architecture

Reinvigorating Englewood, Chicago Through New Public Spaces and Mixed-Income Housing , Givan Carrero, Architecture

Architectural Agency Through Real Estate Development , Hitali Gondaliya, Architecture

Multimodal Transit and a New Civic Architecture , Samuel Bruce Hill, Architecture

Rethinking The Suburban Center , Andrew Jones, Architecture

Resilient Urbanism: Bridging Natural Elements & Sustainable Structures in a Post-Industrial Urban Environment , Nicholas McGee, Architecture

Adaptive Airport Architecture , Yash Mehta, Architecture

Rethinking School Design to Promote Safety and Positivity , Emily Moreau, Architecture

The Built Environment and Well-Being: Designing for Well-Being in Post-Industrial Communities During the Age of Urbanization , Tyler O'Neil, Architecture

Brutalism and the Public University: Integrating Conservation into Comprehensive Campus Planning , Shelby Schrank, Architecture

Spatial Design for Behavioral Education , Madeline Szczypinski, Architecture

Theses from 2019 2019

THERAPEUTIC COMMUNITY: FOR REFUGEES , Raghad Alrashidi, Architecture

From Archaic To contemporary : Energy Efficient Adaptive Reuse of Historic Building , Nisha Borgohain, Architecture

(RE)Developing Place: The Power of Narrative , Kinsey Diomedi, Architecture

Rethinking Ambulatory Care Delivery , Senada Dushaj, Architecture

Photosynthesizing the Workplace: A Study in Healthy and Holistic Production Spaces , Kaeli Howard, Architecture

Museum Design As A Tool For A City , Cunbei Jiang, Architecture

Architecture and Wilderness: An Exchange of Order , Ashley Lepre, Architecture

Cross-Species Architecture: Developing an Architecture for Rehabilitative Learning Through the Human-Canine Relationship , Jake Porter, Architecture

Intermodal Transit Terminal: Integrating the Future of Transit into the Urban Fabric , Guy Vigneau, Architecture

Theses from 2018 2018

Bangladeshi Cultural Center: for the Bangladeshi Population Living in New York City , Sabrina Afrin, Architecture

THE ENHANCEMENT OF LEARNING THROUGH THE DESIGN PROCCESS: RENOVATING THE FORT RIVER ELEMENTARY SCHOOL IN AMHERST, MA , Reyhaneh Bassamtabar, Architecture

LEARNING SPACES: DISCOVERING THE SPACES FOR THE FUTURE OF LEARNING , Michael Choudhary, Architecture

ARCHITECTURAL SYNERGY: A FACILITY FOR LIFELONG LEARNING IN ACADEMIA AND PRACTICE , Ryan Rendano, Architecture

Resilient Architecture: Adaptive Community Living in Coastal Locations , Erica Shannon, Architecture

Theses from 2017 2017

New York City 2050: Climate Change and Future of New York | Design for Resilience , Abhinav Bhargava, Architecture

The Performance of Light: Exploring the Impact of Natural Lighting in the New UMass School of Performance , Dylan Brown, Architecture

Regional Expression In The Renovation Of Remote Historic Villages , Jie chen, Architecture

An Incremental Intervention In Jakarta: An Empowering Infrastructural Approach For Upgrading Informal Settlements , Christopher H. Counihan, Architecture

UMASS Dining Hall. A Path to Resiliency , Lukasz Czarniecki, Architecture

LIVING CORE OF THE FUTURE: PROPOSING NEW APPROACH FOR THE FUTURE OF RESIDENTIAL COMPLEX IN METROPOLITAN AREAS , Mahsa G. Zadeh, Architecture

HUMANITY IN A CHILDREN’S CANCER HOSPITAL , Sara Jandaghi Jafari, Architecture

Designing Symbiosis for the New Church Community , Evan Janes, Architecture

A Visible History: A Synthesis of Past, Present and Future Through the Evocation of Memory Within Historic Contexts , Nicholas Jeffway, Architecture

Creating A Community A New Ecological, Economical, and Social Path to Uniting a Community , Andrew Stadnicki, Architecture

Z-Cube: Mobile Living for Feminist Nomads , Zi Ye, Architecture

Theses from 2016 2016

Music and Architecture: An Interpresence , Rachel J. Beesen, Architecture

Intervening in the Lives of Internally Displaced People in Colombia , Amy L. Carbone, Architecture

Designing Waste Creating Space: A Critical Examination Into Waste Reduction Through Building Techniques, Architectural Design, and Systems , Courtney M. Carrier, Architecture

Umass September 11 Intervention , Mohamad Farzinmoghadam, Architecture

Merging Social Science and Neuroscience in Architecture: Creating a Framework to Functionally Re-integrate Ex-Convicts , Kylie A. Landrey, Architecture

From Shelters to Long Living Communities , Yakun Liang, Architecture

Building Hope: A Community + Water Initiative, La Villa de San Francisco, Honduras , Christopher D. Mansfield, Architecture

THE SPATIALITY IN STORYTELLING , Xiang Yu, Architecture

Innovation of the Residential Buildings and Community in the Emerging City Rongcheng , Xing Yu, Architecture

Art and Life - Make invisible visible in Cao changdi village, Beijing, China , peng zhang, Architecture

Theses from 2015 2015

The Dialogue of Craft and Architecture , Thomas J. Forker, Architecture

MOSQUE IN THE VALLEY: A SPACE FOR SPIRITUAL GATHERING & CULTURAL LEARNING , Nabila Iqbal, Architecture

EXPLORATION OF CONNECTIVITY BETWEEN URBAN PLAZA AND MIXED USE BUILDINGS , Youngduk Kim, Architecture

Design Of A Housing For Urban Artisan-Living Work , Fahim Mahmud, Architecture

Membranes and Matrices: Architecture as an Interface , Nayef Mudawar, Architecture

Building for the Future: Revitalization through Architecture , Rebecca N. Perry, Architecture

Developing Maker Economies in Post-Industrial Cities: Applying Commons Based Peer Production to Mycelium Biomaterials , Grant R. Rocco, Architecture

Design of Children's Event and Cutural Center in Osu, Accra, Ghana , Rudi Somuah, Architecture

Sustainable Design of Student Centers Retrofitting and Adaptive Reuse of UMass Student Union , Tianye Song, Architecture

Design/Build in Architectural Education: studying community-focused curriculum , Matthew K. Sutter, Architecture

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Explore Thesis projects from the Class of 2021

Review Book:  https://issuu.com/mitarchitecture/docs/20-01-05_marchthesisbookletsqsinglep  

Master of Architecture (M.Arch) Website:  https://www.mitmarchthesis.com/theses

Post -arium Arditha Auriyane Advisor: Mariana Ibanez

Priced Out of Paradise :  Reconsidering cooperatives in response to climate gentrification in Miami’s communities of color Adiel Alexis Benitez Advisor: Miho Mazereeuw

To Know is to Empower :  Chagos Institute of Environmental Humanities Chen Chu Advisor: Miho Mazereew

Reclaiming the Estranged :  Reimagining the Architecture of the Excess Sydney Cinalli Advisor: Brandon Clifford, Deborah Garcia

Ferrous Futures :  Scenario Planning for Global Steel Charlotte D'Acierno, Clarence Lee, Jaehun Woo Advisor: Mariana Ibanez

Seven Ways of Reading The House of the Seven Gables Isadora Dannin Advisor: Mark Jarzombek

Gardens of Resistance Nynika Jhaveri Advisor: Azra Aksamija

After Aura :  Authorship, Automation, Authenticity Kailin J. Jones Advisor: Azra Aksamija

The Factory of Coexistence Melika Konjicanin Advisor: Cristina Parreño Alonso

Screen Time Jeffrey Landman Advisor: Rania Ghosn

Architecture for Revision Emma Pfeiffer Advisor: Rosalyne Shieh

Thorough David Allen White Advisor: Mark Jarzombek

Spring 2021

Review Book:  https://issuu.com/mitarchitecture/docs/21-05-21_allthesisbookletpages

Master of Architecture (M.Arch) Website:  https://mit-march-sp21.com/

The Houseful(l)ness of Public Space Xio Alvarez (M.Arch & MCP) Advisor: Miho Mazereeuw, Larry Vale

Still Standing :  Cooperative strategies for the renovation of Soviet mass housing Ben Hoyle, Eytan Levi (M.Arch & MSRED) Advisor: Ana Miljački

Concetividad Alegal :  Remaking and Resilience in the bay of Havana        Lucas Igarzabal, Marissa Concetta Waddle Advisor: Hans Tursack

M.I.celium mexicanus :  Rejecting Modernity through Zapotec Futurism Lynced Torres Advisor: Sheila Kennedy View project site here!

Heirlooms :  In Search of the Fifth Ecology Erin Wong Advisor: Sheila Kennedy

Building / Unbuilding   Andrew Younker Advisor: Azra Akšamija

Space of Mind :  The Hidden Architecture in the Time of Pandemic Ziyu Xu Advisor: Axel Killian

Master of Science in Architecture Studies (SMArchS)

SMArchS Architecture + Urbanism

Third Landscape Dries Carmeliet Advisor: Rania Ghosn

Mediating Chana :  Seeding Synergies Between Doves and Development Eakapob Huangthanapan Advisor: Miho Mazereeuw

Mokumitsu Districts in Tokyo :  Urban Renewal by Housing Cooperatives against Disaster Risk Ryuhei Ichikura Advisor: Miho Mazereeuw

To Build Home and To Live In (U)Hygge Wuyahuang Li Advisor: Mark Jarzombek

Collecting Ideals :  Re-Envisioning Ejidos as Climate-Action Platforms Luis Alberto Meouchi Velez Advisor: Lorena Bello Gomez, Nicholas de Monchaux

Made in Rural China Siyuan Sheng Advisor: Brent Ryan

Generative Urban Design toward Thermal Synergy :  Inspire sustainable urban configuration under distributive heating & cooling schemes Qianqian Wan Advisor: Caitlin Mueller

SMArchS Architecture Design

Velvet Garage :  Narratives of an Education in Architecture Marianna Gonzalez-Cervantes Advisor: Liam O'Brien

Nightrise :  Through the Valley of Jabal ‘Amil’s Shadow Mohamad Nahleh Advisor: Sheila Kennedy

SMArchS Building Technology

Mass Balance :  Design Strategies for Lightweight, Thermally Massive Construction Systems Eduardo Gascón Alvarez Advisor: Caitlin Mueller

Evaluating Overheating Preventative Measures in Residential Buildings and Passive Survivability Yesufu Oladipo Advisor: Les Norford

SMArchS Computation

A Machine Learning Model for Understanding How Users Value Designs :  Applications for Designers and Consumers Jeremy Bilotti (SMArchS Computation & SM in CS) Advisor: Terry Knight

The Untold Narratives Rania Sameh Kaadan Advisor: Terry Knight

Sonic Others :  Metaphorical Sonification of Collective Events Wonki Kang Advisor: Axel Killian

Networking Knowledge and Experience :  An Instrumental System for the Personal Development of Individual Designers Bowen Lu Advisor: George Stiny

Sonic Urban Transformations :  A Computational Model to Study and Represent Temporal Changes in the Walking Experience Elina Oikonomaki Advisor: Terry Knight

Monstrous Space :  Architectural Production in an Age of Algorithms Alexandra Waller Advisor: Larry Sass

Investigating Design Intentions :  Use of Eye Tracking and Machine Leearning to Study Perception of Architecture Xiaoyun Zhang Advisor: Takehiko Nagakura

SMArchS History, Theory & Criticism

"A Great Civilizing Agent" :  Architecture at MIT, Drawing Education, and Boston's Cultural Elite, 1865-1881 Katherine Dubbs Advisor: Arindam Dutta

Surveilling Sin :  Locating Sodomy in the Early Modern Florentine Bathhouse Aidan Flynn Advisor: Kristel Smentek, Jodi Cranston

SMArchS Aga Khan Program

Fractured and Dissolved, Architecture Ablaze :  Towards an Understanding of Ayeneh-Kari in Iranian Palaces Reza Daftarian Advisor: Nasser Rabbat

Scripting Inclusion Amanda Merzaban Advisor: Renee Green

Master of Science in Building Technolgy (SMBT)

Using Urban Building Energy Modeling to Meet Carbon Emission Targets :  A Case Study of Oshkosh, Wisconsin Zachary Berzolla Advisor: Christoph Reinhart

Early Design Stage Building Lifecycle Analysis (LCA) of Cost & Carbon Impact :  A Seamless Addition to the Conceptual Design Process Jingyi Liu Advisor: Jeremy Gregory, Randy Kirchain, Les Norford

Machine Learning for Human Design :  Developing Next Generation Sketch-Based Tools Bryan Ong Wen Xi (SMBT & MEng in CEE) Advisor: Caitlin Mueller

On the Relationship Between Spatial-Temporal Outdoor Thermal Comfort Simulations and Bike Ridership Elizabeth Young Advisor: Christoph Reinhart

Bachelor of Science in Art and Design (BSAD)

Digital Narratives for Self-Therapy Rachel Seo Yeon Kwak Advisor: Lee Moreau

Digital Communities x Collaborative Storytelling Clare Liut (BSAD & SB in 2A) Advisor: Mikael Jakobsson

Concrete Alternatives for Large Scale Additive Manufacturing Chloe Nelson-Arzuaga Advisor: Skylar Tibbits

Image Credits:

01. Ferrous Futures. Courtesy of Charlotte D’Acierno, Clarence Lee and Jaehun Woo (MArch).

02. Space of Mind. Courtesy of Ziyu Xu (MArch).

03. Nightrise. Courtesy of Mohamad Nahleh (SMArchS Architecture Design)

04. Untold Narratives. Courtesy of Rania Kaadan (SMArchS Computation).

05. Mediating Chana. Courtesy of Eakapob Huangthanapan (SMArchS Urbanism).

06. To Build Home and To Live In (U)Hygge. Courtesy of Wuyahuang Li (SMArchS Urbanism).

07. Concetividad Alegal. Courtesy of Lucas Igarzabal and Marissa Concetta Waddle (MArch).

08. The Houseful(l)ness of Public Space. Courtesy of Xio Alvarez (MArch + MCP).

09. Mass Balance. Courtesy of Eduardo Gascón Alvarez (SMArchS Building Technology).

10. Early Design Stage Building Lifecycle Analysis (LCA) of Cost & Carbon Impact. Courtesy of Jingyi Liu (SMBT).

Published July 1, 2021

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Princeton University Library

Finding architecture dissertations & theses: home, theses & dissertations @ princeton and elsewhere.

Princeton Specific

Dissertations & Theses : Covers scholarship from most U.S. universities with some international coverage. Full text coverage begins with 1997+ but indexing includes scholarship dating back to 1861. To search PU Dissertations, follow this link   to a subset of the Proquest Dissertations. 

SoA Design Theses: The School of Architecture maintains an archive of student theses from 1930s through the present. To search the index of projects or access the collection, contact the Visual Resources Curator . This collection includes both graduate and undergraduate projects. 

Princeton Senior Theses Database : A search catalog of senior theses written from 1929 through the present. Approximately 60 000 records are included but not all departments are represented (SoA is). Searchable by author, advisor, department, or year. The Mudd Manuscript Library collects and maintains the primary copies.

SoA Library Senior Thesis Collection :  The School of Architecture Library has a small subset of SoA senioir theses.  These essays can be found in the library Main Catalog by an author search or by a call number browse search for "Sen. Th." Many of these theses have not been formatted for primary copy but rather include color images, fold-outs, dust jackets, etc. This small collection does not circulate. 

Architecture Theses & Dissertations Beyond Princeton

Harvard's Graduate School of Design : A guide for finding masters theses and doctoral dissertations specific to the GSD. 

MIT Architecture Dissertations & Theses : A basic list organized by author of the thesis or dissertation. Each entry includes the title of the work, brief "where are they now" info, and links to the works in MIT's Barton catalog.

UC-Berkeley's Guide to Architecture & Environmental Design Theses and Dissertations: Explains how you can find these works in the UCB system.

Architecture Association's School of Architecture Theses: Theses can be searched via the online catalogue by selecting the 'AA Theses' menu option from the upper left-hand drop-down menu.

Georgia Tech College of Architecture Theses & Dissertations Database

UMass-Amherst's Architecture Masters Theses Collection

Illinois Institute of Technology's College of Architecture Thesis Collection

UIUC's Depts. of Landscape Architecture and Urban Planning Checklist: l inks to pages with basic details about theses, projects, and dissertations from the Departments of Landscape Architecture and Urban Planning up to 2006 (update pending). THis link will take you to the dedicated Landscape Architecture Thesis Database .

Institutional Repositories or Scholarly Commons - freely accessible research archived and disseminated

eCommons@Cornell : The OPEN collection is available to the general public, including the full text. The CLOSED collection is not available outside Cornell and only the citation and abstract are available at Cornell.

Scholarly Commons - Univ. of Pennsylvania : Browse and in some cases access the full text to theses and dissertations from Penn programs and professional schools.

Other Resources

ADT (Australiasian Digital Theses Program) : This search portal provides searching, browsing, and access to theses and dissertations produced in Australia.

Biblioteca Digital de Teses e Dissertacoes : A search tool for accessing theses and dissertations produced in Brazilian universities.

Cybertesis : Sponsored by UNESCO and Fonds Francophone des Inforoutes, Cybertesis is a project between the Université de Montréal, the Université de Lyon2, the University of Chile and 32 universities of Europe, Africa and Latin America . Simultaneous searches through a single Web interface may retrieve more than 50.000 full text theses stored in 27 different servers and university repositories, by means of the use of OAI protocol (Open Archives Initiative) as a service provider (metadata harvesting).

DART-Europe E-theses Portal : A discovery service for open access research theses awarded by European universities.

DiVA : This portal provides access to dissertations, theses, and research publications written at 26 institutions in Scandinavia.

EThOS : Electronic Theses Online Service (EThOS) offers free access, in a secure format, to the full text of electronically stored UK theses--a rich and vast body of knowledge.

Foreign Doctoral Dissertations Database : The Center for Research Libraries has more than 800,000 cataloged foreign doctoral dissertations representing more than 90 countries and over 1200 institutions.

Index to Theses: A comprehensive listing of theses with abstracts accepted for higher degrees by universities in the United Kingdom and Ireland since 1716. 589,028 theses in collection (355,862 of which have abstracts)

NARCIS: This search portal provides access to theses and dissertations produced in the Netherlands, as well as access to a variety of other research and data sets.

National ETD Portal (South Africa): This search portal provides access to dissertations and theses produced in South Africa.

RCAAP - Repositório Científico de Acesso Aberto de Portugal: The RCAAP 's mission is to promote, support and facilitate the adoption of the open access movement in Portugal. RCAAP The project aims to: increase the visibility , accessibility and dissemination of academic activity and Portuguese scientific research , facilitating the management and access to information about scientific production and integrate Portugal into a set of international initiatives.  This portal offers a  union catalog with digital contents from more than 30 institutions.

Theses Canada : A union catalog of Canadian theses and dissertations, in both electronic and analog formats, is available through the search interface on this portal.

• Last Updated: Dec 18, 2023 3:32 PM
• URL: https://libguides.princeton.edu/arch_theses

10 Versatile Architecture Model Materials (& Why So)

You have come up with an idea for a design, and now it is time to take that great idea and turn it into something tangible – how do you do it?

The immediate answer is simple: a model.

The overall solution is a bit more involved and requires foresight and a few critical questions:

What are the design’s physical qualities?

How detailed do you want this model?

Are you trying to get a point across with a conceptual model, or are you trying to convey every nuance of an architectural work-of-art?

Asking these questions is essential for the sake of finding your purpose, sure, but they also guide you to something you may have overlooked. The materials you are going to use to build your model mean a great deal.

So, what material do architects use to build models?

As cliché as it sounds, it depends – on the types of models you are making and the purpose you want them to achieve for you.

Read on to find your material match.

It is cheap, it is plentiful, and it is probably within arm’s reach if you are currently seated at a desk. It does not take any special equipment to assemble a paper model, except maybe some tape and scissors.

Furthermore, due to its unmatched accessibility, it is one of the quickest ways to convert those creative neural impulses into something you have a physical copy of before you forget.

With practice, a paper model can convey a decent deal of detail, thanks to its thin and flexible nature. In many ways, accessibility alone makes paper almost perfect for concept models.

You are not restricted to printer paper, either. Sulfite paper (commonly construction or drawing paper) and cardstock paper can offer different useful qualities for building your model.

The former offers incredible flexibility for stress-free, 3d curvature while the latter offers impeccable sturdiness compared to printer paper and sulfite paper.

2. Cardboard

Also incredibly cheap and plentiful, cardboard often comes free with your Amazon purchase, although you still may want to consider purchasing some from a craft shop.

If cardstock paper is not quite sturdy enough for your applications, cardboard should fulfill the duties wonderfully.

Although it is not quite up to par when compared to the delightful array of colors you have with cardstock, a cardboard model can look good and will serve you well for some time – so long as you are not planning on bending it and making an accurate topographical mock-up.

3. Balsa Wood

A more expensive option than plain-old paper, but a worthwhile investment if you want to amp up the detail in your model without pulling your hair out with an uncooperative material.

With Balsa wood, you have the option to sand, paint, and varnish it for added aesthetic appeal.

It takes precision and patience (splinters are no fun) to build a model, but the result can be highly complex, even including the detailed framework of a building in the form of a working model.

It is wood, after all, a common material in building actual structures.

It does not look too bad either, making it a classy choice for your design – one of the main reasons it is very popular among architecture students despite its price.

Foam is the king of flexibility, soft and malleable. This material comes in extremely useful for building large-scale models fast.

It is effortless to cut and lightweight, so you can build substantially larger models with foam than other materials without the model becoming too heavy to transport easily.

It also comes in all shapes, unlike the materials mentioned above which tend to be confined to flat, board-like shapes.

Carving large three-dimensional models with only one piece of foam (goodbye glue) is an easy possibility for quick and effective conceptual models.

However, if details are hugely important, foam’s softness may not be entirely up to your standards.

With the right equipment, plastic is easily the most versatile architectural modeling material on this list, applicable for anything between a quick concept model and a highly detailed presentation model.

The material itself is cheap and ubiquitous, a staple of modern society. You can cut it, melt it, and cast it to create a variety of shapes.

Plastic is also compatible with 3d printing, meaning you can build a model with CAD software on your computer and create a physical copy of that model without doing any hands-on work, making it a material that hearkens to the needs of the future.

Plastic checks the boxes for affordability, convenience, versatility, and detail.

If you lived in some cruel dystopia where you had to choose only one material for all of your modeling needs, plastic would be a solid choice.

6. Perspex / Acrylic Sheets

You may have heard of Perspex before (or maybe you are perplexed). Perspex is a prevalent producer of acrylic sheets and other acrylic products (a.k.a. plexiglass).

Acrylic sheets are commonly used as a substitute for fragile glass in transparent tabletops, windows, skylights, and more.

They are durable and lightweight, and are thus popularly used in furniture, boats, electronics, and even museum display cases – clearly an excellent material!

It stands to reason that Perspex / acrylic sheets are up to the job and ready to deliver when it comes to architectural models. And if durability is a keystone of your modeling project, acrylic sheets can take many beatings and retain their structural integrity.

A quick scroll through Perspex’s website ( source ) is enough to awe you with its beautiful applications. Just be prepared to invest as the material is not exactly the cheapest thing on this list.

7. Corrugated Board

Often confused with cardboard, corrugated board is a multi-layered paperboard material (think heavy-duty moving boxes) while cardboard is one layer (think cereal boxes).

Corrugated board comfortably fills the niche between affordability and durability.

If your model will have large panes that would become flimsy if made from cardboard, this material will be a good fit.

However, corrugated board is quite ugly compared to the other materials and hard to draw on, making it a poor performer in anything beyond a conceptual model.

If you decide to use it for your model, keep it in a dry location as moisture would love to ruin everything for you.

8. Medium-density Fiberboard

Also commonly referred to in its abbreviated form – MDF – medium-density fiberboard is an engineered wood product that is both denser and smoother than traditional wood.

It typically contains sawdust, resin, and wax.

If you like the idea of using balsa wood for your model but are troubled with the idea of splinters and surface imperfections, MDF can help fill the niche without the drawbacks.

Think of a cheaper version of plywood that is smooth and, well, fun to handle.

Also, it is sturdy and does not enlarge or shrink due to temperature, making it a solid material for use in a presentation model that travels inside and out, from class to class or client to client.

However, being that it is made by essentially pressing a bunch of tiny pieces of wood together (not the most in-depth description), it will not withstand water very well without swelling up.

This material has been around a while, a favorite of many 18 th -century architects for design and model building, and for good reasons.

It is a soft yet sturdy material harvested sustainably from tree bark, making it easy to work with and capable of creating ornate presentation models. It has a low density, is light, bonds easily with glue, and looks incredible.

Cork has a rustic and stone-like quality that is both unique and appealing, especially as a staple for architects who frequently dabble in traditional European styles.

10. Earthenware / Clay

If Imhotep was the mind behind the Egyptian pyramids as historical research is beginning to suggest, he probably built an architectural model out of clay (based on a hunch).

Clay is likely the oldest material for architecture models thanks to it being easily shapable the second it is extracted from the earth.

It may not be the most relevant material for architectural modeling today thanks to technology, but clay’s historical ubiquity should say something about it.

It is incredibly easy to work with if you recall elementary school art class.

Even if you have no experience making material models, you could likely make a rudimentary house right now if a ball of clay just fell on your head.

It is soft when you work with it, but when you are done shaping it, all you need is a little heat (okay, a lot of heat).

Clay deserves respect; it has helped so many minds throughout history convey complex ideas – from Roman pottery to the remarkable Terracotta Army of the imperial Qin Dynasty.

There is no doubt that many of history’s great architects were able to put this wondrous material to profound use.

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The Architecture Thesis of the Year ATY 2020 Unveils Its Winners

• Written by Christele Harrouk
• Published on September 09, 2020

The Architecture Thesis of the Year | ATY 2020 an international architecture thesis competition organized by the Charette , unveiled the winners of this year’s edition. Aiming to “ extend appreciation to the tireless effort and exceptional creativity of student thesis in the fields of Architecture, Urban Design, Landscape and Restoration ”, the contest gathered over 1000 entries from all over the world.

Seeking to encourage young talent by highlighting their ideas and bringing them to the forefront, the competition received over 1000 entries from 104 nations across the world. This year’s jury included Marcio Kogan (Studio MK27, Brazil), Bruno Rollet (Bruno Rollet Architecte, Paris), Daniela Deutsch (Associate Prof., NewSchool of Architecture & Design, California), Dr. Caroline Hachem-Vermette (Assistant Prof, University of Calgary, Canada) and Stefan Kristofferson (Stratic, Germany, Sweden & India). The contest is an annual competition and will be released again in the summer of 2021.

Read on to discover the results of the 2020 edition of the competition and the top three winners.

1st Prize Winner

Isthme // l e chaos sensible.

Dafni Filippa and Meriam Sehimi from Germany

The students from the Technical University of Munich designed a scheme that the jury described as “poetic, based on real-life observations, lightweight and extraordinarily beautiful.” Jurors loved the simplicity and fluidity of the masterplan and how another culture is interpreted. They felt that drawings are adequate, sensitive, and stunning.

2nd Prize Winner

Amazonia trans _ tri _ fronteriza.

Fabiola del Carmen Cruz Ballardo from Peru

Three countries: Peru, Brazil, Bolivia; and two communities: Mancheron, Yamaha. All separated by artificial borders. Nevertheless, they share a common Amazonian culture. There is a will to unite people in this project, to respect different traditions, to propose different places, uniting past present, and future with traditional languages, medical plants, and culture. A « bridge » is created to consolidate this place and to respect it through the world: it can be seen as an SOS. Because this project is also implicitly about the amazon forest: calling to save its richness, be it natural or cultural.

3rd Prize Winner

Philip Springall from the United Kingdom

His project is a multidisciplinary exploration of Alzheimer’s disease, architecture, and neuroscience. Alzheimer’s is a progressive disease that slowly strips away the notions of place, memory, identity, and the self. The project investigates the role that architecture and the built environment can play in improving the lives of those with Alzheimer’s disease. The jury felt that the project “…contemplates a powerful concept which might have great applications in the real world.”

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[Mamba-Survey-2024] Paper list for State-Space-Model/Mamba and it's Applications

Event-AHU/Mamba_State_Space_Model_Paper_List

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Paper list for State-Space-Model and its Applications

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💥 update log.

• [2024.04.15] We release the first version of the survey on state space model [ arXiv ]

Thesis & Surveys

Modeling sequences with structured state spaces , Responsibility: Albert Gu, Publication: [Stanford, California] : [Stanford University], 2023 [ Thesis (330 pages) ] [ PDF ]

State Space Model for New-Generation Network Alternative to Transformers: A Survey , Xiao Wang, Shiao Wang, Yuhe Ding, Yuehang Li, Wentao Wu, Yao Rong, Weizhe Kong, Ju Huang, Shihao Li, Haoxiang Yang, Ziwen Wang, Bo Jiang, Chenglong Li, Yaowei Wang, Yonghong Tian, Jin Tang, 2024 [ PDF ] [ arXiv ]

ST-SSMs: Spatial-Temporal Selective State of Space Model for Traffic Forecasting , arXiv:2404.13257, Zhiqi Shao, Michael G.H. Bell, Ze Wang, D. Glenn Geers, Haoning Xi, Junbin Gao [ Paper ]

The Illusion of State in State-Space Models , arXiv:2404.08819 William Merrill, Jackson Petty, Ashish Sabharwal [ Paper ]

MambaMOS: LiDAR-based 3D Moving Object Segmentation with Motion-aware State Space Model , Kang Zeng, Hao Shi, Jiacheng Lin, Siyu Li, Jintao Cheng, Kaiwei Wang, Zhiyong Li, Kailun Yang [ Paper ] [ Code ]

MambaPupil: Bidirectional Selective Recurrent model for Event-based Eye tracking , CVPR 2024 Workshop (AIS: Vision, Graphics and AI for Streaming) Zhong Wang, Zengyu Wan, Han Han, Bohao Liao, Yuliang Wu, Wei Zhai, Yang Cao, Zheng-jun Zha [ Paper ]

CU-Mamba: Selective State Space Models with Channel Learning for Image Restoration , arXiv:2404.11778, Rui Deng, Tianpei Gu [ Paper ]

State-space Decomposition Model for Video Prediction Considering Long-term Motion Trend , Fei Cui, Jiaojiao Fang, Xiaojiang Wu, Zelong Lai, Mengke Yang, Menghan Jia, Guizhong Liu [ Paper ]

Text-controlled Motion Mamba: Text-Instructed Temporal Grounding of Human Motion , Xinghan Wang, Zixi Kang, Yadong Mu, arXiv:2404.11375 [ Paper ]

HumMUSS: Human Motion Understanding using State Space Models , Arnab Kumar Mondal, Stefano Alletto, Denis Tome, CVPR 2024, arXiv:2404.10880 [ Paper ]

HSIDMamba: Exploring Bidirectional State-Space Models for Hyperspectral Denoising , Yang Liu, Jiahua Xiao, Yu Guo, Peilin Jiang, Haiwei Yang, Fei Wang [ Paper ]

FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion with Mamba , Xinyu Xie, Yawen Cui, Chio-In Ieong, Tao Tan, Xiaozhi Zhang, Xubin Zheng, Zitong Yu [ Paper ] [ Code ]

FreqMamba: Viewing Mamba from a Frequency Perspective for Image Deraining , Zou Zhen, Yu Hu, Zhao Feng [ Paper ]

A Novel State Space Model with Local Enhancement and State Sharing for Image Fusion , Zihan Cao, Xiao Wu, Liang-Jian Deng, Yu Zhong [ Paper ]

Fusion-Mamba for Cross-modality Object Detection , arXiv:2404.09146, Wenhao Dong, Haodong Zhu, Shaohui Lin, Xiaoyan Luo, Yunhang Shen, Xuhui Liu, Juan Zhang, Guodong Guo, Baochang Zhang [ Paper ]

" Linear recurrent units for sequential recommendation. " Yue, Zhenrui, et al. Proceedings of the 17th ACM International Conference on Web Search and Data Mining. 2024. [ Paper ] [ Code ]

State-Space Modeling of Shape-constrained Functional Time Series , Daichi Hiraki, Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa, arXiv:2404.07586 [ Paper ]

HGRN2: Gated Linear RNNs with State Expansion , Zhen Qin, Songlin Yang, Weixuan Sun, Xuyang Shen, Dong Li, Weigao Sun, Yiran Zhong, arXiv:2404.07904 [ Paper ] [ Code ]

MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image Fusion , Zhe Li, Haiwei Pan, Kejia Zhang, Yuhua Wang, Fengming Yu, arXiv:2404.08406 [ Paper ]

SpectralMamba: Efficient Mamba for Hyperspectral Image Classification , Jing Yao, Danfeng Hong, Chenyu Li, Jocelyn Chanussot, arXiv:2404.08489 [ Paper ] [ Code ]

SurvMamba: State Space Model with Multi-grained Multi-modal Interaction for Survival Prediction , Ying Chen, Jiajing Xie, Yuxiang Lin, Yuhang Song, Wenxian Yang, Rongshan Yu, arXiv:2404.08027 [ Paper ]

[2024_143] FusionMamba: Efficient Image Fusion with State Space Model , Siran Peng, Xiangyu Zhu, Haoyu Deng, Zhen Lei, Liang-Jian Deng [ Paper ]

[2024_142] DGMamba: Domain Generalization via Generalized State Space Model , Shaocong Long, Qianyu Zhou, Xiangtai Li, Xuequan Lu, Chenhao Ying, Yuan Luo, Lizhuang Ma, Shuicheng Yan [ Paper ]

[2024_141] ViM-UNet: Vision Mamba for Biomedical Segmentation , Anwai Archit, Constantin Pape [ Paper ] [ Code ]

[2024_140] Simba: Mamba augmented U-ShiftGCN for Skeletal Action Recognition in Videos , Soumyabrata Chaudhuri, Saumik Bhattacharya [ Paper ]

[2024_139] MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection , Haoyang He, Yuhu Bai, Jiangning Zhang, Qingdong He, Hongxu Chen, Zhenye Gan, Chengjie Wang, Xiangtai Li, Guanzhong Tian, Lei Xie [ Paper ]

[2024_138] 3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion , Yixuan Li, Weidong Yang, Ben Fei [ Paper ]

[2024_137] RhythmMamba: Fast Remote Physiological Measurement with Arbitrary Length Videos , Bochao Zou, Zizheng Guo, Xiaocheng Hu, Huimin Ma [ Paper ] [ Code ]

[2024_136] VMambaMorph: a Visual Mamba-based Framework with Cross-Scan Module for Deformable 3D Image Registration , Ziyang Wang, Jian-Qing Zheng, Chao Ma, Tao Guo [ Paper ]

[2024_135] 3DMambaIPF: A State Space Model for Iterative Point Cloud Filtering via Differentiable Rendering , Qingyuan Zhou, Weidong Yang, Ben Fei, Jingyi Xu, Rui Zhang, Keyi Liu, Yeqi Luo, Ying He [ Paper ]

[2024_134] Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentation , Zifu Wan, Yuhao Wang, Silong Yong, Pingping Zhang, Simon Stepputtis, Katia Sycara, Yaqi Xie [ Paper ] [ Code ]

[2024_133] xT: Nested Tokenization for Larger Context in Large Images , Ritwik Gupta, Shufan Li, Tyler Zhu, Jitendra Malik, Trevor Darrell, Karttikeya Mangalam [ Paper ] [ Code ]

[2024_132] Locating and Editing Factual Associations in Mamba , Arnab Sen Sharma, David Atkinson, David Bau [ Paper ]

[2024_131] InsectMamba: Insect Pest Classification with State Space Model , Qianning Wang, Chenglin Wang, Zhixin Lai, Yucheng Zhou [ Paper ]

[2024_130] ChangeMamba: Remote Sensing Change Detection with Spatio-Temporal State Space Model , Hongruixuan Chen, Jian Song, Chengxi Han, Junshi Xia, Naoto Yokoya [ Paper ] [ Code ]

[2024_129] RS-Mamba for Large Remote Sensing Image Dense Prediction , Sijie Zhao, Hao Chen, Xueliang Zhang, Pengfeng Xiao, Lei Bai, Wanli Ouyang [ Paper ] [ Code ]

[2024_128] RS3Mamba: Visual State Space Model for Remote Sensing Images Semantic Segmentation , Xianping Ma, Xiaokang Zhang, Man-On Pun [ Paper ] [ Code ]

[2024_127] SPMamba: State-space model is all you need in speech separation , Kai Li, Guo Chen [ Paper ]

[2024_126] On the reduction of Linear Parameter-Varying State-Space models , E. Javier Olucha, Bogoljub Terzin, Amritam Das, Roland Tóth [ Paper ]

[2024_125] Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model , Qinfeng Zhu, Yuanzhi Cai, Yuan Fang, Yihan Yang, Cheng Chen, Lei Fan, Anh Nguyen [ Paper ] [ Code ]

[2024_124] T-Mamba: Frequency-Enhanced Gated Long-Range Dependency for Tooth 3D CBCT Segmentation , Jing Hao, Lei He, Kuo Feng Hung [ Paper ] [ Code ]

[2024_123] Decision Mamba: Reinforcement Learning via Sequence Modeling with Selective State Spaces , Toshihiro Ota [ Paper ]

[2024_122] RankMamba, Benchmarking Mamba's Document Ranking Performance in the Era of Transformers , Zhichao Xu [ Paper ] [ Code ]

[2024_121] SpikeMba: Multi-Modal Spiking Saliency Mamba for Temporal Video Grounding , Wenrui Li, Xiaopeng Hong, Xiaopeng Fan [ Paper ]

[2024_120] HSIMamba: Hyperpsectral Imaging Efficient Feature Learning with Bidirectional State Space for Classification , Judy X Yang, Jun Zhou, Jing Wang, Hui Tian, Alan Wee Chung Liew [ Paper ] [ Code ]

[2024_119] HARMamba: Efficient Wearable Sensor Human Activity Recognition Based on Bidirectional Selective SSM , Shuangjian Li, Tao Zhu, Furong Duan, Liming Chen, Huansheng Ning, Yaping Wan [ Paper ]

[2024_118] UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation , Renkai Wu, Yinghao Liu, Pengchen Liang, Qing Chang [ Paper ] [ Code ]

[2024_117] MambaMixer: Efficient Selective State Space Models with Dual Token and Channel Selection , Ali Behrouz, Michele Santacatterina, Ramin Zabih [ Paper ]

[2024_116] Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separation , Xilin Jiang, Cong Han, Nima Mesgarani [ Paper ]

[2024_115] STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model , Lincan Li, Hanchen Wang, Wenjie Zhang, Adelle Coster [ Paper ]

[2024_114] Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference , Han Zhao, Min Zhang, Wei Zhao, Pengxiang Ding, Siteng Huang, Donglin Wang [ Paper ]

[2024_113] Music to Dance as Language Translation using Sequence Models , André Correia, Luís A. Alexandre [ Paper ] [ Code ]

[2024_112] CMViM: Contrastive Masked Vim Autoencoder for 3D Multi-modal Representation Learning for AD classification , Guangqian Yang, Kangrui Du, Zhihan Yang, Ye Du, Yongping Zheng, Shujun Wang [ Paper ]

[2024_111] Proprioception Is All You Need: Terrain Classification for Boreal Forests , Damien LaRocque, William Guimont-Martin, David-Alexandre Duclos, Philippe Giguère, François Pomerleau [ Paper ]

[2024_110] ReMamber: Referring Image Segmentation with Mamba Twister , Yuhuan Yang, Chaofan Ma, Jiangchao Yao, Zhun Zhong, Ya Zhang, Yanfeng Wang [ Paper ]

[2024_109] Mechanistic Design and Scaling of Hybrid Architectures , Michael Poli, Armin W Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli [ Paper ]

[2024_108] Model order reduction of deep structured state-space models: A system-theoretic approach , Marco Forgione, Manas Mejari, Dario Piga

[2024_107] Modeling Analog Dynamic Range Compressors using Deep Learning and State-space Models , Hanzhi Yin, Gang Cheng, Christian J. Steinmetz, Ruibin Yuan, Richard M. Stern, Roger B. Dannenberg [ Paper ]

[2024_106] Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation , Jiyuan Yang, Yuanzi Li, Jingyu Zhao, Hanbing Wang, Muyang Ma, Jun Ma, Zhaochun Ren, Mengqi Zhang, Xin Xin, Zhumin Chen, Pengjie Ren [ Paper ] [ Code ]

[2024_105] State Space Models as Foundation Models: A Control Theoretic Overview , Carmen Amo Alonso, Jerome Sieber, Melanie N. Zeilinger [ Paper ]

[2024_104] Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models , Mohammad Shahab Sepehri, Zalan Fabian, Mahdi Soltanolkotabi [ Paper ]

[2024_103] Jamba: A Hybrid Transformer-Mamba Language Model , Opher Lieber, Barak Lenz, Hofit Bata, Gal Cohen, Jhonathan Osin, Itay Dalmedigos, Erez Safahi, Shaked Meirom, Yonatan Belinkov, Shai Shalev-Shwartz, Omri Abend, Raz Alon, Tomer Asida, Amir Bergman, Roman Glozman, Michael Gokhman, Avashalom Manevich, Nir Ratner, Noam Rozen, Erez Shwartz, Mor Zusman, Yoav Shoham [ Paper ] [ Website ] [ Huggingface ]

[2024_102] Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstruction , Qiuhong Shen, Xuanyu Yi, Zike Wu, Pan Zhou, Hanwang Zhang, Shuicheng Yan, Xinchao Wang [ Paper ]

[2024_101] RSMamba: Remote Sensing Image Classification with State Space Model , [ Project ] [ Paper ] [ Code ]

[2024_100] Rotate to Scan: UNet-like Mamba with Triplet SSM Module for Medical Image Segmentation , Hao Tang, Lianglun Cheng, Guoheng Huang, Zhengguang Tan, Junhao Lu, Kaihong Wu [ Paper ]

[2024_099] PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition , Chenhongyi Yang, Zehui Chen, Miguel Espinosa, Linus Ericsson, Zhenyu Wang, Jiaming Liu, Elliot J. Crowley [ Paper ] [ Code ]

[2024_098] Integrating Mamba Sequence Model and Hierarchical Upsampling Network for Accurate Semantic Segmentation of Multiple Sclerosis Legion , Kazi Shahriar Sanjid, Md. Tanzim Hossain, Md. Shakib Shahariar Junayed, Dr. Mohammad Monir Uddin [ Paper ]

[2024_097] VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting , Yujin Tang, Peijie Dong, Zhenheng Tang, Xiaowen Chu, Junwei Liang [ Paper ] [ Code ]

[2024_096] SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series , Badri N. Patro, Vijay S. Agneeswaran [ Paper ] [ Code ]

[2024_095] Repeat After Me: Transformers are Better than State Space Models at Copying , Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach [ Paper ]

[2024_094] H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation , Renkai Wu, Yinghao Liu, Pengchen Liang, Qing Chang [ Paper ] [ Code ]

[2024_093] VL-Mamba: Exploring State Space Models for Multimodal Learning , Yanyuan Qiao, Zheng Yu, Longteng Guo, Sihan Chen, Zijia Zhao, Mingzhen Sun, Qi Wu, Jing Liu [ Paper ] [ Project ] [ Code ]

[2024_092] ProMamba: Prompt-Mamba for polyp segmentation , Jianhao Xie, Ruofan Liao, Ziang Zhang, Sida Yi, Yuesheng Zhu, Guibo Luo [ Paper ]

[2024_091] ZigMa: Zigzag Mamba Diffusion Model , Vincent Tao Hu, Stefan Andreas Baumann, Ming Gui, Olga Grebenkova, Pingchuan Ma, Johannes Fischer, Bjorn Ommer [ Paper ] [ Code ]

[2024_090] On the low-shot transferability of [V]-Mamba , Diganta Misra, Jay Gala, Antonio Orvieto [ Paper ]

[2024_089] Is Mamba Effective for Time Series Forecasting? Zihan Wang, Fanheng Kong, Shi Feng, Ming Wang, Han Zhao, Daling Wang, Yifei Zhang [ Paper ] [ Code ]

[2024_088] VmambaIR: Visual State Space Model for Image Restoration , Yuan Shi, Bin Xia, Xiaoyu Jin, Xing Wang, Tianyu Zhao, Xin Xia, Xuefeng Xiao, Wenming Yang [ Paper ]

[2024_087] Understanding Robustness of Visual State Space Models for Image Classification , Chengbin Du, Yanxi Li, Chang Xu [ Paper ]

[2024_086] Regularization-Based Efficient Continual Learning in Deep State-Space Models , Yuanhang Zhang, Zhidi Lin, Yiyong Sun, Feng Yin, Carsten Fritsche [ Paper ]

[2024_085] TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting , Md Atik Ahamed, Qiang Cheng [ Paper ] [ Code ]

[2024_084] EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba , Xiaohuan Pei, Tao Huang, Chang Xu [ Paper ] [ Code ]

[2024_083] MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models , Zunnan Xu, Yukang Lin, Haonan Han, Sicheng Yang, Ronghui Li, Yachao Zhang, Xiu Li [ Paper ]

[2024_082] LocalMamba: Visual State Space Model with Windowed Selective Scan , Tao Huang, Xiaohuan Pei, Shan You, Fei Wang, Chen Qian, Chang Xu [ Paper ] [ Code ]

[2024_081] VM-UNET-V2 Rethinking Vision Mamba UNet for Medical Image Segmentation , Mingya Zhang, Yue Yu, Limei Gu, Tingsheng Lin, Xianping Tao [ Paper ] [ Code ]

[2024_080] Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding , Guo Chen, Yifei Huang, Jilan Xu, Baoqi Pei, Zhe Chen, Zhiqi Li, Jiahao Wang, Kunchang Li, Tong Lu, Limin Wang [ Paper ] [ Code ]

[2024_079] Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling , Raunaq Bhirangi, Chenyu Wang, Venkatesh Pattabiraman, Carmel Majidi, Abhinav Gupta, Tess Hellebrekers, Lerrel Pinto [ Paper ]

[2024_078] MambaStock: Selective state space model for stock prediction , Zhuangwei Shi [ Paper ] [ Code ]

[2024_077] Simple linear attention language models balance the recall-throughput tradeoff , Simran Arora, Sabri Eyuboglu, Michael Zhang, Aman Timalsina, Silas Alberti, Dylan Zinsley, James Zou, Atri Rudra, Christopher Ré [ Paper ]

[2024_076] LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation , Weibin Liao, Yinghao Zhu, Xinyuan Wang, Chengwei Pan, Yasha Wang, Liantao Ma [ Paper ] [ Code ]

[2024_075] Motion-Guided Dual-Camera Tracker for Low-Cost Skill Evaluation of Gastric Endoscopy , Yuelin Zhang, Wanquan Yan, Kim Yan, Chun Ping Lam, Yufu Qiu, Pengyu Zheng, Raymond Shing-Yan Tang, Shing Shin Cheng [ Paper ]

[2024_074] Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling , Yair Schiff, Chia-Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, Volodymyr Kuleshov [ Paper ]

[2024_073] MD-Dose: A Diffusion Model based on the Mamba for Radiotherapy Dose Prediction , Linjie Fu, Xia Li, Xiuding Cai, Yingkai Wang, Xueyao Wang, Yali Shen, Yu Yao [ Paper ]

[2024_072] Activating Wider Areas in Image Super-Resolution , Cheng Cheng, Hang Wang, Hongbin Sun [ Paper ]

[2024_071] Multichannel Long-Term Streaming Neural Speech Enhancement for Static and Moving Speakers , Changsheng Quan, Xiaofei Li [ Paper ]

[2024_070] A multi-cohort study on prediction of acute brain dysfunction states using selective state space models , Brandon Silva, Miguel Contreras, Sabyasachi Bandyopadhyay, Yuanfang Ren, Ziyuan Guan, Jeremy Balch, Kia Khezeli, Tezcan Ozrazgat Baslanti, Ben Shickel, Azra Bihorac, Parisa Rashidi [ Paper ]

[2024_069] The pitfalls of next-token prediction , Gregor Bachmann, Vaishnavh Nagarajan [ Paper ] [ Code ]

[2024_068] Large Window-based Mamba UNet for Medical Image Segmentation: Beyond Convolution and Self-attention , Jinhong Wang, Jintai Chen, Danny Chen, Jian Wu [ Paper ] [ Code ]

[2024_067] Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM , Zeyu Zhang, Akide Liu, Ian Reid, Richard Hartley, Bohan Zhuang, Hao Tang [ Paper ] [ Project ] [ Code ]

[2024_066] ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes , Zhichao Yang, Avijit Mitra, Sunjae Kwon, Hong Yu [ Paper ] [ Code ]

[2024_065] MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology , Shu Yang, Yihui Wang, Hao Chen [ Paper ] [ Code ]

[2024_064] Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy , Jiuming Liu, Ruiji Yu, Yian Wang, Yu Zheng, Tianchen Deng, Weicai Ye, Hesheng Wang [ Paper ] [ Code ]

[2024_063] VideoMamba: State Space Model for Efficient Video Understanding , Kunchang Li, Xinhao Li, Yi Wang, Yinan He, Yali Wang, Limin Wang, Yu Qiao [ Paper ] [ Code ]

[2024_062] MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models , Zijie Fang, Yifeng Wang, Zhi Wang, Jian Zhang, Xiangyang Ji, Yongbing Zhang [ Paper ]

[2024_061] Video Diffusion State Space Models , Zhengcong Fei, Mingyuan Fan, Changqian Yu, Jusnshi Huang, [ Paper ] [ Code ]

[2024_060] Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models , Chengkai Liu, Jianghao Lin, Jianling Wang, Hanzhou Liu, James Caverlee [ Paper ]

[2024_059] MedMamba: Vision Mamba for Medical Image Classification , Yubiao Yue, Zhenzhang Li [ Paper ] [ Code ]

[2024_058] Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models , Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George Cristian-Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando De Freitas, Caglar Gulcehre [ Paper ]

[2024_057] Gated Linear Attention Transformers with Hardware-Efficient Training , Songlin Yang, Bailin Wang, Yikang Shen, Rameswar Panda, Yoon Kim [ Paper ] [ Code ]

[2024_056] DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models , [ Paper ] [ Code ]

[2024_055] The Hidden Attention of Mamba Models , [ Paper ] [ Code ]

[2024_054] MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection , Tianxiang Chen, Zhentao Tan, Tao Gong, Qi Chu, Yue Wu, Bin Liu, Jieping Ye, Nenghai Yu [ Paper ] [ Code ]

[2024_053] Point Could Mamba: Point Cloud Learning via State Space Model , Tao Zhang, Xiangtai Li, Haobo Yuan, Shunping Ji, Shuicheng Yan [ Paper ] [ Code ]

[2024_052] Res-VMamba: Fine-Grained Food Category Visual Classification Using Selective State Space Models with Deep Residual Learning , Chi-Sheng Chen, Guan-Ying Chen, Dong Zhou, Di Jiang, Dai-Shi Chen [ Paper ] [ Code ]

[2024_051] MambaMIR: An Arbitrary-Masked Mamba for Joint Medical Image Reconstruction and Uncertainty Estimation , Jiahao Huang, Liutao Yang, Fanwen Wang, Yinzhe Wu, Yang Nan, Angelica I. Aviles-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang [ Paper ] [ Code ]

[2024_050] MambaIR: A Simple Baseline for Image Restoration with State-Space Model , Hang Guo, Jinmin Li, Tao Dai, Zhihao Ouyang, Xudong Ren, Shu-Tao Xia [ Paper ] [ Code ]

[2024_049] State Space Models for Event Cameras , Nikola Zubić, Mathias Gehrig, Davide Scaramuzza [ Paper ]

[2024_048][ICLR 2024] FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores , Daniel Y Fu, Hermann Kumbong, Eric Nguyen, Christopher Re [ Paper ]

[2024_047] Variational quantization for state space models , Etienne David, Jean Bellot, Sylvain Le Corff [ Paper ]

[2024_046] Efficient Long Sequence Modeling via State Space Augmented Transformer , Simiao Zuo, Xiaodong Liu, Jian Jiao, Denis X Charles, Eren Manavoglu, Tuo Zhao, Jianfeng Gao [ Paper ]

[2024_045][ICLR 2024] Robustifying State-space Models for Long Sequences via Approximate Diagonalization , Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson [ Paper ]

[2024_044] From generalization analysis to optimization designs for state space models , Fusheng Liu, Qianxiao Li [ Paper ]

[2024_043] A 2-Dimensional State Space Layer for Spatial Inductive Bias , Ethan Baron, Itamar Zimerman, Lior Wolf [ Paper ]

[2024_042][ICLR 2024] Hieros: Hierarchical Imagination on Structured State Space Sequence World Models , Paul Mattes, Rainer Schlosser, Ralf Herbrich [ Paper ]

[2024_041] S4++: Elevating Long Sequence Modeling with State Memory Reply , [ Paper ]

[2024_040][Rejected by ICLR 2024] Mamba: Linear-Time Sequence Modeling with Selective State Spaces , Albert Gu, Tri Dao [ Paper ] [ Mamba: The Hard Way ] [ annotated-mamba ]

[2024_039][ICLR 2024] Gated recurrent neural networks discover attention , Nicolas Zucchet, Seijin Kobayashi, Yassir Akram, Johannes Von Oswald, Maxime Larcher, Angelika Steger, Joao Sacramento [ Paper ]

[2024_038][ICLR 2024] GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling , Tobias Katsch [ Paper ]

[2024_037][ICLR 2024] Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors , Ido Amos, Jonathan Berant, Ankit Gupta [ Paper ]

[2024_036] [ICLR 2024] Mastering Memory Tasks with World Models , Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar [ Paper ] [ Project Page ] [ Code ]

[2024_035] Spectral State Space Models , Naman Agarwal, Daniel Suo, Xinyi Chen, Elad Hazan [ Paper ]

[2024_034] Graph Mamba: Towards Learning on Graphs with State Space Models , Ali Behrouz, Farnoosh Hashemi [ Paper ]

[2024_033] Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks , Jongho Park, Jaeseung Park, Zheyang Xiong, Nayoung Lee, Jaewoong Cho, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos [ Paper ]

[2024_032] Is Mamba Capable of In-Context Learning? Riccardo Grazzi, Julien Siems, Simon Schrodi, Thomas Brox, Frank Hutter [ Paper ]

[2024_031] LOCOST: State-Space Models for Long Document Abstractive Summarization , Florian Le Bronnec, Song Duong, Mathieu Ravaut, Alexandre Allauzen, Nancy F. Chen, Vincent Guigue, Alberto Lumbreras, Laure Soulier, Patrick Gallinari [ Paper ] [ Code ]

[2024_030] RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks , Haowen Hou, F. Richard Yu [ Paper ] [ Code ]

[2024_029] BlackMamba: Mixture of Experts for State-Space Models , Quentin Anthony, Yury Tokpanov, Paolo Glorioso, Beren Millidge [ Paper ] [ Code ]

[2024_028] Recurrent Distance Filtering for Graph Representation Learning , Yuhui Ding, Antonio Orvieto, Bobby He, Thomas Hofmann [ Paper ] [ Code ]

[2024_027] SSM Meets Video Diffusion Models: Efficient Video Generation with Structured State Spaces , Yuta Oshima, Shohei Taniguchi, Masahiro Suzuki, Yutaka Matsuo [ Paper ]

[2024_026] Pan-Mamba: Effective pan-sharpening with State Space Model , Xuanhua He, Ke Cao, Keyu Yan, Rui Li, Chengjun Xie, Jie Zhang, Man Zhou [ Paper ] [ Code ]

[2024_025] Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentation , Ziyang Wang, Chao Ma [ Paper ] [ Code ]

[2024_024] PointMamba: A Simple State Space Model for Point Cloud Analysis , Dingkang Liang, Xin Zhou, Xinyu Wang, Xingkui Zhu, Wei Xu, Zhikang Zou, Xiaoqing Ye, Xiang Bai [ Paper ] [ Code ]

[2024_023] P-Mamba: Marrying Perona Malik Diffusion with Mamba for Efficient Pediatric Echocardiographic Left Ventricular Segmentation , Zi Ye, Tianxiang Chen [ Paper ]

[2024_022] Semi-Mamba-UNet: Pixel-Level Contrastive Cross-Supervised Visual Mamba-based UNet for Semi-Supervised Medical Image Segmentation , Ziyang Wang, Chao Ma [ Paper ]

[2024_021] FD-Vision Mamba for Endoscopic Exposure Correction , Zhuoran Zheng, Jun Zhang, [ Paper ]

[2024_020] Scalable Diffusion Models with State Space Backbone , Zhengcong Fei, Mingyuan Fan, Changqian Yu, Junshi Huang [ Paper ] [ Code ]

[2024_019] Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data , Shufan Li, Harkanwar Singh, Aditya Grover [ Paper ]

[2024_018] Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation , Ziyang Wang, Jian-Qing Zheng, Yichi Zhang, Ge Cui, Lei Li [ Paper ] [ Code ]

[2024_017] MambaTab: A Simple Yet Effective Approach for Handling Tabular Data , Md Atik Ahamed1, Qiang Cheng [ Paper ]

[2024_016] nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model , Haifan Gong, Luoyao Kang, Yitao Wang, Xiang Wan, Haofeng Li [ Paper ] [ Code ]

[2024_015] U-shaped Vision Mamba for Single Image Dehazing , Zhuoran Zheng, Chen Wu [ Paper ]

[2024_014] Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces , Chloe Wang, Oleksii Tsepa, Jun Ma, Bo Wang [ Paper ] [ Code ]

[2024_013] VM-UNet: Vision Mamba UNet for Medical Image Segmentation , Jiacheng Ruan, Suncheng Xiang [ Paper ] [ Code ]

[2024_012] Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining , Jiarun Liu, Hao Yang, Hong-Yu Zhou, Yan Xi, Lequan Yu, Yizhou Yu, Yong Liang, Guangming Shi, Shaoting Zhang, Hairong Zheng, Shanshan Wang [ Paper ] [ Code ]

[2024_011] Ma, Jun, Feifei Li, and Bo Wang. " U-mamba: Enhancing long-range dependency for biomedical image segmentation ." arXiv preprint arXiv:2401.04722 (2024). [ Paper ] [ Code ]

[2024_010] Vivim: a Video Vision Mamba for Medical Video Object Segmentation , Yijun Yang, Zhaohu Xing, and Lei Zhu [ Paper ] [ Code ]

[2024_009] Wang, Junxiong, et al. " MambaByte: Token-free Selective State Space Model. " arXiv preprint arXiv:2401.13660 (2024). [ Paper ] [ Code ]

[2024_008] MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts. Pióro, M., Ciebiera, K., Król, K., Ludziejewski, J., & Jaszczur, S. (2024). arXiv preprint arXiv:2401.04081. [ Paper ]

[2024_007] [ICLR-2024] MASTERING MEMORY TASKS WITH WORLD MODELS [ Paper ]

[2024_006] MambaMorph: a Mamba-based Backbone with Contrastive Feature Learning for Deformable MR-CT Registration , Tao Guo, Yinuo Wang, and Cai Meng [ Paper ] [ Code ]

[2024_005] SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation , [ Paper ] [ Code ]

[2024_003] Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model , Lianghui Zhu1∗, Bencheng Liao1∗, Qian Zhang2, Xinlong Wang3, Wenyu Liu1, Xinggang Wang [ Paper ] [ Code ]

[2024_002] VMamba: Visual State Space Model , Yue Liu1,Yunjie Tian1,Yuzhong Zhao1, Hongtian Yu1, Lingxi Xie2, Yaowei Wang3, Qixiang Ye1, Yunfan Liu1 [ Paper ] [ Code ]

[2024_001] Theoretical Foundations of Deep Selective State-Space Models , Nicola Muca Cirone, Antonio Orvieto, Benjamin Walker, Cristopher Salvi, Terry Lyons [ Paper ]

[2023_018] [CHIL 2023] Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models , Siyi Tang, Jared A. Dunnmon, Liangqiong Qu, Khaled K. Saab, Tina Baykaner, Christopher Lee-Messer, Daniel L. Rubin [ Paper ]

[2023_017] "StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization." Wang, Shida, and Qianxiao Li. arXiv preprint arXiv:2311.14495 (2023). [ Paper ] [ Code ]

[2023_016] State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory , Shida Wang, Beichen Xue [ Paper ]

[2023_015] Spiking Structured State Space Model for Monaural Speech Enhancement . Du, Y., Liu, X., & Chua, Y. (2023). arXiv preprint arXiv:2309.03641. [ Paper ]

[2023_014] Mastering Diverse Domains through World Models , Danijar Hafner,12 Jurgis Pasukonis,1 Jimmy Ba,2 Timothy Lillicrap [ Paper ] [ Code ]

[2023_013] Selective Structured State-Spaces for Long-Form Video Understanding , Jue Wang Wentao Zhu Pichao Wang Xiang Yu Linda Liu Mohamed Omar Raffay Hamid [ Paper ]

[2023_012] Mamba: Linear-Time Sequence Modeling with Selective State Spaces , Albert Gu*1and Tri Dao [ Paper ] [ Github ]

[2023_011] [NeurIPS 2023] Structured State Space Models for In-Context Reinforcement Learning , Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Foerster, Satinder Singh, Feryal Behbahani [ Paper ] [ Code ]

[2023_010] Diffusion Models Without Attention , Jing Nathan Yan, Jiatao Gu, Alexander M. Rush [ Paper ]

[2023_009] Hierarchically Gated Recurrent Neural Network for Sequence Modeling , Zhen Qin, Songlin Yang, Yiran Zhong [ Paper ] [ Code ]

[2023_008] Retentive Network: A Successor to Transformer for Large Language Models , Yutao Sun, Li Dong, Shaohan Huang, Shuming Ma, Yuqing Xia, Jilong Xue, Jianyong Wang, Furu Wei [ Paper ] [ Code ]

[2023_007] Convolutional State Space Models for Long-Range Spatiotemporal Modeling , Jimmy T.H. Smith, Shalini De Mello, Jan Kautz, Scott W. Linderman, Wonmin Byeon [ Paper ] [ Code ]

[2023_006] Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions , Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, Aman Timalsina, David W. Romero, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Re, Stefano Ermon, Yoshua Bengio [ Paper ]

[2023_005] Structured state-space models are deep Wiener models , Fabio Bonassi, Carl Andersson, Per Mattsson, Thomas B. Schön [ Paper ]

[2023_004] Zoology: Measuring and Improving Recall in Efficient Language Models , Simran Arora, Sabri Eyuboglu, Aman Timalsina, Isys Johnson, Michael Poli, James Zou, Atri Rudra, Christopher Ré [ Paper ]

[2023_003] [ICML 2023] Resurrecting Recurrent Neural Networks for Long Sequences , Antonio Orvieto · Samuel Smith · Albert Gu · Anushan Fernando · Caglar Gulcehre · Razvan Pascanu · Soham De [ Paper ]

[2023_002] Hyena Hierarchy: Towards Larger Convolutional Language Models , Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré [ Paper ]

[2023_001] [ICLR 2023] Simplified State Space Layers for Sequence Modeling , Jimmy T.H. Smith, Andrew Warrington, Scott Linderman [ Paper ]

[2022_009] [ECCV-2022] Long Movie Clip Classification with State-Space Video Models , Md Mohaiminul Islam, Gedas Bertasius [ Paper ] [ Code ]

[2022_008] [NIPS-2022] "S4nd: Modeling images and videos as multidimensional signals with state spaces." Nguyen, Eric, et al. Advances in neural information processing systems 35 (2022): 2846-2861. [ Paper ] [ Code ]

[2022_007] [Pre-training] Wang, J., Yan, J. N., Gu, A., & Rush, A. M. (2022). Pretraining without attention . arXiv preprint arXiv:2212.10544. [ Paper ] [ Code ]

[2022_006] Long Range Language Modeling via Gated State Spaces , Harsh Mehta1∗ Ankit Gupta2 Ashok Cutkosky3 Behnam Neyshabur1 [ Paper ]

[2022_005] [ICML2022] It’s Raw! Audio Generation with State-Space Models , Karan Goel, Albert Gu, Chris Donahue, and Christopher R´e [ Paper ]

[2022_004] Diagonal State Spaces are as Effective as Structured State Spaces , Ankit Gupta˚Albert Gu Jonathan Berant [ Paper ]

[2022_003] How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections , Albert Gu∗†, Isys Johnson∗‡, Aman Timalsina‡, Atri Rudra‡, and Christopher R´e† [ Paper ]

[2022_002] On the Parameterization and Initialization of Diagonal State Space Models , Albert Gu†, Ankit Gupta‡, Karan Goel†, and Christopher R´e† [ Paper ]

[2022_001] Efficiently Modeling Long Sequences with Structured State Spaces , Albert Gu, Karan Goel, Christopher Ré [ Paper ] [ The Annotated S4 ]

Year 2021 and Before

[2021_003] Efficiently Modeling Long Sequences with Structured State Spaces , Albert Gu, Karan Goel, and Christopher R´e [ Paper ] [ Code ]

[2021_002] HiPPO: Recurrent Memory with Optimal Polynomial Projections , Albert Gu∗†, Tri Dao∗†, Stefano Ermon†, Atri Rudra‡, and Christopher Ré† [ Paper ] [ Code ]

[2021_001] Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers , Albert Gu†, Isys Johnson†, Karan Goel†, Khaled Saab†, Tri Dao†, Atri Rudra‡, and Christopher Ré† [ Paper ]

Related Models

Diffusion-RWKV: Scaling RWKV-Like Architectures for Diffusion Models , Zhengcong Fei, Mingyuan Fan, Changqian Yu, Debang Li, Junshi Huang [ Paper ]

"Retentive network: A successor to transformer for large language models." Sun, Yutao, et al. arXiv preprint arXiv:2307.08621 (2023). [ Paper ] [ Code ]

TLS-RWKV: Real-Time Online Action Detection with Temporal Label Smoothing . Zhu, Z., Shao, W. & Jiao, D. Neural Process Lett 56, 57 (2024). [ Paper ]

RRWKV: Capturing Long-range Dependencies in RWKV , Leilei Wang [ Paper ]

RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks , Haowen Hou, F. Richard Yu [ Paper ] [ Code ]

Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures , Yuchen Duan, Weiyun Wang, Zhe Chen, Xizhou Zhu, Lewei Lu, Tong Lu, Yu Qiao, Hongsheng Li, Jifeng Dai, Wenhai Wang [ Paper ] [ Code ]

RWKV: Reinventing RNNs for the Transformer Era , Bo Peng, Eric Alcaide, Quentin Anthony, Alon Albalak, Samuel Arcadinho, Stella Biderman, Huanqi Cao, Xin Cheng, Michael Chung, Matteo Grella, Kranthi Kiran GV, Xuzheng He, Haowen Hou, Jiaju Lin, Przemyslaw Kazienko, Jan Kocon, Jiaming Kong, Bartlomiej Koptyra, Hayden Lau, Krishna Sri Ipsit Mantri, Ferdinand Mom, Atsushi Saito, Guangyu Song, Xiangru Tang, Bolun Wang, Johan S. Wind, Stanislaw Wozniak, Ruichong Zhang, Zhenyuan Zhang, Qihang Zhao, Peng Zhou, Qinghua Zhou, Jian Zhu, Rui-Jie Zhu [ Paper ]

Other Useful URLs

• [ awesome-ssm-ml ]
• [ Awesome-Mamba-Papers ]
• [ XiudingCai/Awesome-Mamba-Collection ]
• [ Awesome-state-space-models ] Collection of papers/repos on state-space models.
• [ mamba-minimal ] Simple, minimal implementation of the Mamba SSM in one file of PyTorch.
• [ mamba.py ] A simple and efficient Mamba implementation in PyTorch and MLX.
• [ Introduction to State Space Models (SSM) ]
• [ State-Space Modelling by Kevin Kotzé ]
• [ Structured State Spaces: Combining Continuous-Time, Recurrent, and Convolutional Models ]
• [ A Visual Guide to Mamba and State Space Models ---An Alternative to Transformers for Language Modeling ] FEB 19, 2024, by MAARTEN GROOTENDORST.
• [ Structured State Spaces: A Brief Survey of Related Models ] by Albert Gu, Karan Goel, Khaled Saab, and Chris Ré
• [ Video-Tutorial ] [ Mamba and S4 Explained: Architecture, Parallel Scan, Kernel Fusion, Recurrent, Convolution, Math ] by Umar Jamil [ Mamba_Slides.pdf ]

If you think this survey is helpful, please feel free to leave a star ⭐️ and cite our paper:

Star History

Contributors 5

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Deep Learning for Ordinary Differential Equations and Predictive Uncertainty

Deep neural networks (DNNs) have demonstrated outstanding performance in numerous tasks such as image recognition and natural language processing. However, in dynamic systems modeling, the tasks of estimating and uncovering the potentially nonlinear structure of systems represented by ordinary differential equations (ODEs) pose a significant challenge. In this dissertation, we employ DNNs to enable precise and efficient parameter estimation of dynamic systems. In addition, we introduce a highly flexible neural ODE model to capture both nonlinear and sparse dependent relations among multiple functional processes. Nonetheless, DNNs are susceptible to overfitting and often struggle to accurately assess predictive uncertainty despite their widespread success across various AI domains. The challenge of defining meaningful priors for DNN weights and characterizing predictive uncertainty persists. In this dissertation, we present a novel neural adaptive empirical Bayes framework with a new class of prior distributions to address weight uncertainty.

In the first part, we propose a precise and efficient approach utilizing DNNs for estimation and inference of ODEs given noisy data. The DNNs are employed directly as a nonparametric proxy for the true solution of the ODEs, eliminating the need for numerical integration and resulting in significant computational time savings. We develop a gradient descent algorithm to estimate both the DNNs solution and the parameters of the ODEs by optimizing a fidelity-penalized likelihood loss function. This ensures that the derivatives of the DNNs estimator conform to the system of ODEs. Our method is particularly effective in scenarios where only a set of variables transformed from the system components by a given function are observed. We establish the convergence rate of the DNNs estimator and demonstrate that the derivatives of the DNNs solution asymptotically satisfy the ODEs determined by the inferred parameters. Simulations and real data analysis of COVID-19 daily cases are conducted to show the superior performance of our method in terms of accuracy of parameter estimates and system recovery, and computational speed.

In the second part, we present a novel sparse neural ODE model to characterize flexible relations among multiple functional processes. This model represents the latent states of the functions using a set of ODEs and models the dynamic changes of these states utilizing a DNN with a specially designed architecture and sparsity-inducing regularization. Our new model is able to capture both nonlinear and sparse dependent relations among multivariate functions. We develop an efficient optimization algorithm to estimate the unknown weights for the DNN under the sparsity constraint. Furthermore, we establish both algorithmic convergence and selection consistency, providing theoretical guarantees for the proposed method. We illustrate the efficacy of the method through simulation studies and a gene regulatory network example.

In the third part, we introduce a class of implicit generative priors to facilitate Bayesian modeling and inference. These priors are derived through a nonlinear transformation of a known low-dimensional distribution, allowing us to handle complex data distributions and capture the underlying manifold structure effectively. Our framework combines variational inference with a gradient ascent algorithm, which serves to select the hyperparameters and approximate the posterior distribution. Theoretical justification is established through both the posterior and classification consistency. We demonstrate the practical applications of our framework through extensive simulation examples and real-world datasets. Our experimental results highlight the superiority of our proposed framework over existing methods, such as sparse variational Bayesian and generative models, in terms of prediction accuracy and uncertainty quantification.

Degree Type

• Doctor of Philosophy

Campus location

• West Lafayette

Advisor/Supervisor/Committee Chair

Additional committee member 2, additional committee member 3, additional committee member 4, usage metrics.

• Statistics not elsewhere classified
• Deep learning

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Powering the future: meet the scaling energy demands of generative ai.

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Marc Bolitho is the CEO of Recogni , developer of AI-based inference processing solutions for Gen AI and intelligent autonomous platforms.

The massive increase in data center power consumption to support generative AI technology including Large Language Models (LLMs) is challenging America’s electrical grid in ways not seen since the widespread adoption of central home air conditioning in the 1960s.

"The simultaneous growth of electric cars and AI, both of which need electricity, both of which need voltage transformers—I think, is creating a tremendous demand for electrical equipment and for electrical power generation," Tesla CEO Elon Musk said during an interview at the Bosch Connected World conference in February.

Per a January 2023 McKinsey report , data center power consumption in the US market is expected to jump from 17 gigawatts (GW) in 2017 to 35 GW by 2030—we’ll need the output equivalent of nine Hoover Dams to account for that additional 18 GW. To increase power production and keep up with ever increasing demand, utilities are working to modernize aging power grids that have outlived their operational lifetimes while companies like Microsoft have begun contracting directly with renewable energy suppliers .

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Training even a single large language model (LLM) takes months and costs millions of dollars. Some industry experts estimate that training GPT-4 took up to six months running on thousands of GPUs and consuming multiple GWh of energy.

What’s more, the AI data centers that train these models consume four times as much electricity as data centers hosting cloud applications. That added power draw comes from the graphics processing units (GPUs) that perform the networked parallel processing operations required by LLMs like ChatGPT and DALL-E 3. Intel and AMD central processing units (CPUs) typically draw between 300 and 400 watts . NVIDIA’s H100 GPU , on the other hand, draws 700 watts .

As Paul Churnock, Principal Electrical Engineer at Microsoft, noted in a January LinkedIn post , NVIDIA estimates it will sell around 2 million H100s in 2024. The combined draw from those GPUs would outpace the residential power consumption of Phoenix, Arizona, and rival that of Houston, Texas—a city of 2.2 million people.

GPUs also generate significantly more waste heat than CPUs, requiring upgraded cooling systems. For example, HVAC-based cooling solutions are sufficient for a CPU server room with rack power densities up to 30 kW. However, today’s GPU racks offer power densities exceeding 40kW , necessitating liquid cooling, which is extremely resource-intensive to operate. Microsoft reportedly consumed 6.4 million cubic meters of water to cool its data centers in 2022— a 34% jump from the previous year —amidst its intensive AI development efforts.

These factors make retrofitting existing data centers a challenge as the existing power infrastructure only supports a quarter of the GPUs as it would CPUs. Such retrofits require additional hardware and cooling system installations, and potentially engineering work on the building itself. The center’s networking requirements will also increase due to added traffic load from the increased compute capacity.

LLMs need regular re-training with updated information to keep their knowledge bases current and to maintain response accuracy. While there currently is large demand for compute to train the many new models, as they gain acceptance and usage grows, then demand for inference compute will far exceed that for training. Essentially, the more users that you have, and the more applications that you have using generative AI, the more inference you're going to need.

Efficient Chip Architecture Is The Key To AI’s Power Predicament

Just as widening freeways doesn’t alleviate traffic congestion , simply increasing the amount of electricity we produce won’t solve our generative AI’s power problems. Doing so will certainly exacerbate the negative environmental impacts of America’s existing power generation infrastructure and pose a significant challenge to meeting the nation’s carbon-zero goals . Thus, it is vitally important that we improve the efficiency of our data center compute infrastructure.

A 2021 study by Google found that, given the same square footage, employing more efficient model and processor architecture can reduce a data center’s carbon footprint anywhere from 100 to 1,000 times , so why are we focusing on doing more of the same when we could find a better, more efficient way to compute AI data?

We should instead be focused on achieving the densest and most efficient compute by reimagining the architecture of the chip itself. By increasing the efficiency of the compute through better architecture, we can pack more compute into a smaller device package, while still drawing significantly less power than the same amount of compute on a larger, less-efficient chip.

That means you can put a tremendous amount more compute in a given data center, more than you could with existing solutions. You’d effectively need to build fewer data centers and could even retrofit existing installations to achieve a higher level of performance. They’d consume less power by increasing efficiency ( terra flops per watt ) which would reduce the need for liquid cooling in the data center and water consumption as well.

The end result significantly benefits all of us—far less capital expenditure, lower operating costs and lower energy consumption for the same amount of compute.

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