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In This Article Expand or collapse the "in this article" section Social Work Research Methods

Introduction.

History of Social Work Research Methods
Feasibility Issues Influencing the Research Process
Measurement Methods
Existing Scales
Group Experimental and Quasi-Experimental Designs for Evaluating Outcome
Single-System Designs for Evaluating Outcome
Program Evaluation
Surveys and Sampling
Introductory Statistics Texts
Advanced Aspects of Inferential Statistics
Qualitative Research Methods
Qualitative Data Analysis
Historical Research Methods
Meta-Analysis and Systematic Reviews
Research Ethics
Culturally Competent Research Methods
Teaching Social Work Research Methods

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Social Work Research Methods by Allen Rubin LAST REVIEWED: 14 December 2009 LAST MODIFIED: 14 December 2009 DOI: 10.1093/obo/9780195389678-0008

Social work research means conducting an investigation in accordance with the scientific method. The aim of social work research is to build the social work knowledge base in order to solve practical problems in social work practice or social policy. Investigating phenomena in accordance with the scientific method requires maximal adherence to empirical principles, such as basing conclusions on observations that have been gathered in a systematic, comprehensive, and objective fashion. The resources in this entry discuss how to do that as well as how to utilize and teach research methods in social work. Other professions and disciplines commonly produce applied research that can guide social policy or social work practice. Yet no commonly accepted distinction exists at this time between social work research methods and research methods in allied fields relevant to social work. Consequently useful references pertaining to research methods in allied fields that can be applied to social work research are included in this entry.

This section includes basic textbooks that are used in courses on social work research methods. Considerable variation exists between textbooks on the broad topic of social work research methods. Some are comprehensive and delve into topics deeply and at a more advanced level than others. That variation is due in part to the different needs of instructors at the undergraduate and graduate levels of social work education. Most instructors at the undergraduate level prefer shorter and relatively simplified texts; however, some instructors teaching introductory master’s courses on research prefer such texts too. The texts in this section that might best fit their preferences are by Yegidis and Weinbach 2009 and Rubin and Babbie 2007 . The remaining books might fit the needs of instructors at both levels who prefer a more comprehensive and deeper coverage of research methods. Among them Rubin and Babbie 2008 is perhaps the most extensive and is often used at the doctoral level as well as the master’s and undergraduate levels. Also extensive are Drake and Jonson-Reid 2007 , Grinnell and Unrau 2007 , Kreuger and Neuman 2006 , and Thyer 2001 . What distinguishes Drake and Jonson-Reid 2007 is its heavy inclusion of statistical and Statistical Package for the Social Sciences (SPSS) content integrated with each chapter. Grinnell and Unrau 2007 and Thyer 2001 are unique in that they are edited volumes with different authors for each chapter. Kreuger and Neuman 2006 takes Neuman’s social sciences research text and adapts it to social work. The Practitioner’s Guide to Using Research for Evidence-based Practice ( Rubin 2007 ) emphasizes the critical appraisal of research, covering basic research methods content in a relatively simplified format for instructors who want to teach research methods as part of the evidence-based practice process instead of with the aim of teaching students how to produce research.

Drake, Brett, and Melissa Jonson-Reid. 2007. Social work research methods: From conceptualization to dissemination . Boston: Allyn and Bacon.

This introductory text is distinguished by its use of many evidence-based practice examples and its heavy coverage of statistical and computer analysis of data.

Grinnell, Richard M., and Yvonne A. Unrau, eds. 2007. Social work research and evaluation: Quantitative and qualitative approaches . 8th ed. New York: Oxford Univ. Press.

Contains chapters written by different authors, each focusing on a comprehensive range of social work research topics.

Kreuger, Larry W., and W. Lawrence Neuman. 2006. Social work research methods: Qualitative and quantitative applications . Boston: Pearson, Allyn, and Bacon.

An adaptation to social work of Neuman's social sciences research methods text. Its framework emphasizes comparing quantitative and qualitative approaches. Despite its title, quantitative methods receive more attention than qualitative methods, although it does contain considerable qualitative content.

Rubin, Allen. 2007. Practitioner’s guide to using research for evidence-based practice . Hoboken, NJ: Wiley.

This text focuses on understanding quantitative and qualitative research methods and designs for the purpose of appraising research as part of the evidence-based practice process. It also includes chapters on instruments for assessment and monitoring practice outcomes. It can be used at the graduate or undergraduate level.

Rubin, Allen, and Earl R. Babbie. 2007. Essential research methods for social work . Belmont, CA: Thomson Brooks Cole.

This is a shorter and less advanced version of Rubin and Babbie 2008 . It can be used for research methods courses at the undergraduate or master's levels of social work education.

Rubin, Allen, and Earl R. Babbie. Research Methods for Social Work . 6th ed. Belmont, CA: Thomson Brooks Cole, 2008.

This comprehensive text focuses on producing quantitative and qualitative research as well as utilizing such research as part of the evidence-based practice process. It is widely used for teaching research methods courses at the undergraduate, master’s, and doctoral levels of social work education.

Thyer, Bruce A., ed. 2001 The handbook of social work research methods . Thousand Oaks, CA: Sage.

This comprehensive compendium includes twenty-nine chapters written by esteemed leaders in social work research. It covers quantitative and qualitative methods as well as general issues.

Yegidis, Bonnie L., and Robert W. Weinbach. 2009. Research methods for social workers . 6th ed. Boston: Allyn and Bacon.

This introductory paperback text covers a broad range of social work research methods and does so in a briefer fashion than most lengthier, hardcover introductory research methods texts.

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Advanced Qualitative Research Methods in Social Work: Constructivist Grounded Theory Method and Phenomenology: From Design to Data Analyses - Elective

Prior graduate coursework in qualitative methods is required (e.g. SWK 6307)

This advanced research methods course will delve into two major qualitative designs – constructivist grounded theory method and phenomenology . Students will learn key assumptions and methods of these two approaches to facilitate ethical engagement with vulnerable research participants on sensitive topics, while also working towards the highest standards of qualitative rigor. The course will provide students opportunities to familiarize themselves with the nuances of these methodologies, and implications for data collection and analysis. Textual data will be the units of analyses. Open, axial and selective coding will be taught as practiced in the grounded theory tradition, as well as how to conduct thematic analysis for phenomenological based data. Interpretive methods and trustworthiness will be covered as part of the research process. Further, hands on practice will be required for research interviewing and in using NVivo software. Students will be provided data for analyses or may use their own.

This course will be delivered in a seminar style format therefore, students should be comfortable in participating in class discussions, as well as in self-directed learning outside of the classroom. Creative thinking and brainstorming will be encouraged for engaging in this discovery oriented, inductive paradigm.

Foundations of Social Work Research

(4 reviews)

Rebecca L. Mauldin

ISBN 13: 9781648169915

Publisher: Mavs Open Press

Language: English

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Reviewed by LaToya Smith-Jones, Adjunct Professor, University of Texas at Arlington on 3/26/24

Comprehensiveness rating: 5 see less

The textbook covers various topics that are familiar to the Social Work profession. There are relatable examples given within the book, which allow Social Work students to understand discussions through the lens of an actual practitioner. Each section provides an area where research vocabulary is listed and reviewed, as well as examples to deepen the understanding of the vocabulary used.

Content Accuracy rating: 5

The information presented in the textbook is presented with accuracy. Bias was not noticed within the text.

Relevance/Longevity rating: 5

The information presented within the textbook was up-to-date. Classical studies were also included in the textbook. The classical studies allow the students to understand the historical influence regarding the research process.

Clarity rating: 5

The textbook provides examples and a separate vocabulary section in order to understand the jargon and technical terminology. individuals who do not have a research background will be able to comprehend the information written.

Consistency rating: 5

The textbook is consistent regarding terminology and framework. Each section builds upon the previous section.

Modularity rating: 5

Each section is broken up according to the topic of the chapter. Each chapter is broken up in sections, which allows for an easier read.

Organization/Structure/Flow rating: 5

The chapters are presented in a logical and clear fashion. The information presented within the textbook builds upon itself. Students are first introduced to background information regarding the topic and then they are given information regarding the application of the information shared.

Interface rating: 5

There were not any interface issues.

Grammatical Errors rating: 5

There were not any grammatical errors noted.

Cultural Relevance rating: 5

Information within the text was inclusive and included examples of various ethnicities and backgrounds.

The textbook is excellent to use for students who do not have a research background. The manner in which the information is presented and laid out assists with aiding students' understanding.

Reviewed by Quentin Maynard, Assistant Professor, University of Southern Indiana on 11/30/22

This text covers topics that social work students need to understand to be consumers of research. The author and contributors include current real work examples to help emphasize the different topics. Integrating the chapter on Real World Research throughout the text might help emphasize to students that engaging in research is necessary to our profession, even as practitioners.

The content was accurate and error-free.

The content of the text was up-to-date and included information relevant to social work research. Since the main author solicited contributions from colleagues at their institution, updates and changes would likely be relatively straightforward.

The book seemed accessible for individuals with limited research experience. Key words were defined in the text and included in a glossary at the end of each section and the text.

The text was consistent in style and organization. Chapter subsections have specific learning objectives allowing students to know what will be covered in each chapter. Doing this reduces bloat and increases clarity for readers.

The text did not appear to be structured in a way that was overwhelming or difficult to follow.

The structure of the book was logical.

The digital pdf and the online versions of the text were intuitive and easy to navigate. I did not notice any issues with the interface in either format.

No writing or grammar errors noted.

The text is culturally sensitive. It includes a content advisory at the beginning of each chapter which allows students to be aware of specific topics (e.g., racism, sexism, and poverty) discussed or mentioned in the chapter. While this text was adapted for students at a specific university, the authors include topics that reach much farther than that audience. The examples included cover a diverse set of people and situations.

This is a comprehensive text that allows students the opportunity to learn how to be consumers of social work research. While practice evaluation might not be the scope of this text, other than the chapter on Real World Research, including discussions about how students might apply the concepts of each chapter in social work practice. The structure of the book allows students to see the research that their professors are engaging in and might make research more accessible to social work students and practitioners

Reviewed by Matt Walsh, Assistant Professor of Social Work, Marian University on 12/30/21

This textbook covers all the aspects of research you would expect for an introduction to social work research. It uses classic examples of past research to highlight the importance of ethics in research. It also does a good job of discussing both quantitative and qualitative research as well as single system designs and program evaluation. My one critique as someone who does qualitative research is that it mentions the importance of trustworthiness and rigor in qualitative research but does not mention how a research can achieve this. However, it does go into other elements like coding and it would not be hard to provide student with supplemental materials about memoing or peer debriefing as examples and to be fair, it is hard to put everything in just one chapter.

All components are accurately described and well-written. The glossary at the end of each section is helpful for key words. The text appears to be error-free and unbiased.

There are links to recent examples which highlights the real world aspect of research.

This text is clear in its description of research and its major components. Certain aspects like causality get a little advanced for a introduction to research book but there are good visual to aid in students' understanding of some of the more complicated concepts. (Please note that I am reviewing this with BSW students in mind, MSW students may not find some of these sections as overwhelming as I suspect my students might).

The book is very well structured and consistent throughout.

The text is well structured and organized as a whole and in terms of each chapter and each section with the chapters.

The topics follow the order of most other foundational research books I have seen and have a logical flow to them.

I did not find any interface issues.

I could not see any grammatical errors.

There are good examples throughout that display an effort to have inclusivity, diversity, and equity in this text.

I feel like this book would provide students with a good understanding about research and could be used interchangeably with other foundational/introduction books on the market, especially if the professor is familiar with teaching research and has already established a good foundation (quizzes, lecture slides, assignments, activities, etc.).

Reviewed by Vivian Miller, Assistant Professor in Social Work, Bowling Green State University on 1/5/21

The text Foundations of Social Work Research covers social work research comprehensively and appropriately. Across twelve chapters, the author begins by introducing research, the science behind research and how this translates to the profession of social work, and the importance of understanding research as it applies to social work practice across all system levels. In addition to comprehensive chapters, the text contains a glossary, practice behavior indices, bibliography, derivative notes, and links by each chapter.

This text is an accurate text that is error free. This text is extremely well-written and includes real-life examples, drawing on written contributions from social work faculty across practice settings and populations, as well as students at the masters and doctoral levels.

Much of research methods and the process is overall static, however the author does an incredible job to provide timely, relevant, and applicable examples throughout the text to ensure that this version will not be obsolete within a short period of time.

This text is clearly written and is easy to move through. This text contains chapters and sub-chapters. I’d recommend this book for a higher-level undergraduate program or graduate program (e.g., MSW), as there is technical terminology used. Additionally, the author provides a glossary at the back of the text, hyperlinked to each chapter on the web-version. Moreover, there are definitions highlighted at center page throughout the text.

This text is very consistent. Chapters build on one another and are written in clear order.

The use of subheadings throughout allows this text to be separated into smaller reading sections. For instance, if an instructor wanted to assign reading for “Probability sampling,” this topic can be readily extracted from the full text. A student can understand this topic area despite being separated from the text as context is provided to the reader in each sub-chapter. The use of bolded words, images, examples, and hyperlinks throughout make the text easy to separate and digest.

This text is very well-organized and moves through each section in a step-wise process building on each previous content area.

There are no interface issues in the text. Images display well, as well as key takeaway and glossary charts throughout each chapter.

The text contains no grammatical errors.

This text is culturally sensitive. Examples across all system levels (e.g., micro, messo, and macro) are inclusive of a variety of races, ethnicities, and backgrounds.

Highly recommend this text for a Social Work research course.

Chapter One: Introduction to research
Chapter Two: Linking methods with theory
Chapter Three: Ethics in social work research
Chapter Four: Design and causality
Chapter Five: Defining and measuring concepts
Chapter Six: Sampling
Chapter Seven: Survey research
Chapter Eight: Experimental design
Chapter Nine: Unique features of qualitative research
Chapter Ten: Unobtrusive research
Chapter Eleven: Real-world research
Chapter Twelve: Reporting research

Ancillary Material

About the book.

This textbook was created to provide an introduction to research methods for BSW and MSW students, with particular emphasis on research and practice relevant to students at the University of Texas at Arlington. It provides an introduction to social work students to help evaluate research for evidence-based practice and design social work research projects. It can be used with its companion, A Guidebook for Social Work Literature Reviews and Research Questions by Rebecca L. Mauldin and Matthew DeCarlo, or as a stand-alone textbook.

About the Contributors

Rebecca L. Mauldin , Ph.D

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Quantitative Research Methods for Social Work: Making Social Work Count, Barbra Teater, John Devaney, Donald Forester, Jonathan Scourfield and John Carpenter

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Hugh McLaughlin, Quantitative Research Methods for Social Work: Making Social Work Count, Barbra Teater, John Devaney, Donald Forester, Jonathan Scourfield and John Carpenter, The British Journal of Social Work , Volume 52, Issue 3, April 2022, Pages 1793–1795, https://doi.org/10.1093/bjsw/bcaa116

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I remember sharing a lift with a Professor from America at a joint IFSW/IASSW World Social Work Conference who taught research methods. After chatting about teaching research methods, he informed me gleefully that his students are taught qualitative methods first. However, after they get to him, none of them leave his classroom without being ‘converted to quantitative methods’! At this point, he got off the lift leaving our discussion in the air.

This book arose from funding from the Economic and Social Research Council to address the quantitative skills gap in the social sciences. The grants were applied for under the auspices of the Joint University Council Social Work Education Committee to upskill social work academics and develop a curriculum resource with teaching aids. I was saddened to discover that many of the free resources are no longer available and wondered if anything could be done to remedy this.

The book is unusual for the UK in that its major focus is on quantitative methods unlike other social work research methods books which tend to cover both qualitative and quantitative methods ( Campbell et al. , 2017; Smith, 2009). Until this book came along many of us will have been happy using non-social work research methods texts to learn about quantitative methods ( Bryman, 2015). This authoritative text offers a fresh and imaginative approach to teaching quantitative methods. It is set out in an incremental and easily accessible format with a series of exercises and critical thinking boxes with suggested readings at the end of each chapter. The exercises and critical thinking questions are well thought out with a full answer to each at the back of the book—thus making it really useful for those of us who teach research methods. It is also aimed at social work academics, social work students and practitioners who want to learn more about quantitative approaches, where they are useful, how they can be read and understood, and how they can be applied to their setting.

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Practice research methods in social work: Processes, applications and implications for social service organisations

Author: Emmeline Chuang Michael J. Austin Sarah Carnochan Publication date: September 30, 2022 Publication type: Journal Article Citation: McBeath, B., Austin, M. J., Carnochan, S., & Chuang, E. (2022). Practice research methods in social work: Processes, applications and implications for social service organisations. The British Journal of Social Work, 52(6), 3328-3346.

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The University of Minnesota College of Science and Engineering (CSE) welcomes 25 faculty members this 2023-24 academic year—on its way to achieving its goal to hire 60 faculty in three years.

The expertise of this new group of CSE researchers and educators is broad. They range in areas such as hybrid intelligence systems, the reconstruction of past environments and climates, electric machines and magnetic levitation, reinforced concrete structures, and mathematical models to predict the electronic properties of novel materials.

Meet our new science and engineering faculty:

Rene Boiteau is an assistant professor of chemistry. He joins Minnesota from Oregon State University, where he held a joint faculty appointment in the Pacific Northwest National Laboratory. Boiteau earned a bachelor’s in chemistry at Northwestern University, a master’s in earth sciences at University of Cambridge, and a Ph.D. in chemical oceanography at Massachusetts Institute of Technology and Woods Hole Oceanographic Institution. Much of his work is focused on developing analytical chemical approaches, especially mass spectrometry.

Zhu-Tian Chen is an assistant professor of computer science and engineering. He received his bachelor’s in software engineering from South China University of Technology and Ph.D. in computer science from Hong Kong University of Science and Technology. Prior to Minnesota, Chen served as a postdoctoral fellow at Harvard University and postdoctoral researcher at the University of California San Diego. His recent work focuses on enhancing human-data and human-AI interactions in both AR/VR environments—with applications in sports, data journalism, education, biomedical, and architecture.

Gregory “Greg” Handy is an assistant professor of mathematics . He comes to Minnesota from the University of Chicago, where he was a postdoctoral scholar in the Departments of Neurobiology and Statistics. As an applied mathematician and theoretical biologist, Handy’s research strives to use biological applications as inspiration to create new mathematical techniques, and to combine these techniques with classical approaches to examine the mechanisms driving biological processes. This fall, he is teaching Math 2142: Elementary Linear Algebra.

Jessica Hoover is a professor of chemistry. She joins the University of Minnesota from West Virginia University, where she has been a faculty member since 2012. Hoover’s interest in catalysis has been the focus of her work since her undergraduate studies. She graduated with a bachelor’s from Harvey Mudd College before arriving at the University of Washington to pursue her Ph.D. She was a postdoctoral researcher at the University of Wisconsin, Madison.

Harman Kaur is an assistant professor of computer science and engineering—and a University of Minnesota alumna (2016 bachelor’s in computer science). Her research areas are human-centered artificial intelligence, explainability and interpretability, and hybrid intelligence systems. She is affiliated with the GroupLens Research Lab, a group of faculty and students in her department that’s focused on human computing interaction. Prior to Minnesota, Kaur served as a graduate researcher in the interactive Systems Lab and comp.social Lab at the University of Michigan, where she received both her master’s and Ph.D.

Yulong Lu is an assistant professor of mathematics. He joins the faculty from University of Massachusetts, Amherst. Lu received his Ph.D. in mathematics and statistics at the University of Warwick. His research lies at the intersection of applied and computational mathematics, statistics, and data sciences. His recent work is focused on the mathematical aspects of deep learning. This fall, Lu is teaching Math 2573H: Honors Calculus III to undergraduates and Math 8600: Topics in Applied Mathematics, Theory of Deep Learning to graduate students.

Ben Margalit is an assistant professor of physics and astronomy. As a theoretical astrophysicist, he studies the fundamental physics of star explosions, collisions and other examples of intergalactic violence such as a black hole passing near a galaxy and “shredding it to spaghetti.” As part of his job, Margalit works closely with observational astronomers in selecting the kinds of places to look for transient events. He holds bachelor’s and master’s degrees from the Hebrew University of Jerusalem, and a Ph.D. from Columbia University.

Maru Sarazola is an assistant professor of mathematics. She joins Minnesota from Johns Hopkins University, where she was a J.J. Sylvester Assistant Professor. Sarazola received her Ph.D. from Cornell University. Her research is focused on algebraic topology—specifically, her interest lies in homotopy theory (a field that studies and classifies objects up to different notions of "sameness") and category theory (“the math of math,” which looks to abstract all structures to study their behavior). This fall, she is teaching Math 5285H: Honors Algebra I.

Eric Severson is an associate professor of mechanical engineering—and University of Minnesota alumnus (2008 bachelor’s and 2015 Ph.D. in electrical engineering). He returns to his alma mater after being on the University of Wisconsin-Madison faculty for six years. Severson leads research in electric machines and magnetic levitation, with a renewed focus in addressing grand challenges in energy and sustainability through multidisciplinary collaborations. His interests include extreme efficiency, bearingless machines, flywheel energy storage, and electric power grid technology.

Kelsey Stoerzinger is an associate professor of chemical engineering and materials science. She was on the faculty at Oregon State University, with a joint appointment in the Pacific Northwest National Laboratory. She studies the electrochemical transformation of molecules into fuels, chemical feedstocks, and recovered resources. Her research lab designs materials and processes for the storage of renewable electricity. Stoerzinger holds a bachelor’s from Northwestern University, master’s from University of Cambridge, and Ph.D. from MIT.

Lynn Walker is a professor—and the L.E. Scriven Chair in the Department of Chemical Engineering and Materials Science. Previously, she was on the faculty at Carnegie Mellon University. Her research focuses on developing the tools and fundamental understanding necessary to efficiently process soft materials and complex fluids. This expertise is being used to develop systematic approaches to incorporate sustainable feedstocks in consumer products. Walker holds a bachelor’s from the University of New Hampshire and Ph.D. from the University of Delaware. She was a postdoctoral researcher at Katholieke Universiteit Leuven in Belgium.

Alexander “Alex” Watson is an assistant professor of mathematics—and former University of Minnesota postdoctoral researcher in the School of Mathematics. Watson earned his Ph.D. at Columbia University. He works on mathematical models used to predict the electronic properties of materials, especially novel 2D materials such as graphene and twisted multilayer “moiré materials.” In summer 2022 and 2023, he presented at the U’s MathCEP Talented Youth Mathematics Program on topics related to materials research at the University of Minnesota.

Anna Weigandt is an assistant professor of mathematics. She comes to Minnesota from the Massachusetts Institute of Technology, where she was an instructor. Weigandt completed her Ph.D. at the University of Illinois, and she was a postdoctoral assistant professor in the Center for Inquiry Based Learning at University of Michigan. She works in algebraic combinatorics, specifically Schubert calculus. This fall 2023, she is teaching Math 5705: Enumerative Combinatorics.

Michael Wilking is a professor of physics—and University of Minnesota alumnus (2001 bachelor’s in chemical engineering). He holds a master’s and Ph.D. from the University of Colorado. Prior to his return to the Twin Cities campus, Wilking served on the faculty at Stony Brook University. He completed his post-doc at TRIUMF, Canada's national particle accelerator center. Wilking was part of the Stony Brook research team honored with the 2016 Breakthrough Prize in Fundamental Physics.

Benjamin "Ben" Worsfold is an assistant professor of civil engineering —and a licensed professional engineer in both California and Costa Rica. His research interest lies in large-scale structural testing, finite element analysis of reinforced concrete structures, and anchoring to concrete. Worsfold earned his master’s and Ph.D. from the University of California, Berkeley, and bachelor’s from the University of Costa Rica.

Yogatheesan Varatharajah is an assistant professor of computer science and engineering —and a visiting scientist in neurology at the Mayo Clinic. His research lies broadly in machine learning for health. Varatharajah earned his master’s and Ph.D. from the University of Illinois Urbana-Champaign. Prior to Minnesota, he was a research assistant professor of bioengineering at the University of Illinois and faculty affiliate for the Center for Artificial Intelligence Innovation with the National Center for Supercomputing Applications.

Starting in January 2024:

Emily Beverly is an incoming assistant professor of earth sciences. Prior to joining the University of Minnesota, she was on the faculty at University of Houston. She earned a bachelor’s from Trinity University, a master’s from Rutgers University, and a Ph.D. from Baylor University. Beverly was a postdoctoral researcher at Georgia State University and University of Michigan. Her research focuses on understanding environmental drivers of human and hominin evolution. Beverly uses stable isotopes and geochemistry to answer questions about past and future climates with a firm foundation in sedimentary geology and earth surface processes.

Alexander “Alex” Grenning is an assistant professor of chemistry. He comes to Minnesota from the University of Florida, where he was a tenured faculty. Grenning earned a bachelor’s in chemistry and music from Lake Forest College, and a Ph.D. in organic chemistry from the University of Kansas. He was a postdoctoral researcher at Boston University. His work is focused on chemical synthesis and drug discovery.

Yu Cao is an incoming professor of electrical and computer engineering. Prior to Minnesota, Cao was a professor at Arizona State University. He holds a bachelor’s in physics from Peking University and a master’s in biophysics plus a Ph.D. in electrical engineering and computer sciences from the University of California-Berkeley. His research includes neural-inspired computing, hardware design for on-chip learning, and reliable integration of nanoelectronics. Cao served as associate editor of the Institute of Electrical and Electronics Engineers’s monthly Transactions on CAD .

Edgar Peña is an incoming assistant professor of biomedical engineering—and a University of Minnesota alumnus (2017 Ph.D. in biomedical engineering). He is a neuromodulation scholar who is interested in vagus nerve stimulation. Peña earned his bachelor’s degrees in electrical engineering and biomedical engineering from the University of California, Irvine. During his doctoral studies at the University of Minnesota Twin Cities, he used computational models to optimize deep brain stimulation.

Seongjin Choi is an incoming assistant professor of civil engineering. He received his bachelor’s, master’s, and Ph.D. from the Korea Advanced Institute of Science and Technology. He was a postdoctoral researcher at McGill University. His work involves using data analytics to draw valuable insights from urban mobility data and applying cutting-edge AI technologies in the field of transportation.

Pedram Mortazavi is an incoming assistant professor of civil engineering— and a licensed structural engineer in Canada . His interests lie in structural resilience, steel structures, large-scale testing, development of damping and isolation systems, advanced simulation methods, and hybrid simulation. Mortazavi holds a bachelor’s from the University of Science and Culture in Iran, a master’s from Carleton University in Ottawa, and Ph.D. from the University of Toronto.

Gang Qiu is an incoming assistant professor of electrical and computer engineering. He received his bachelor’s degree from Peking University in microelectronics and his Ph.D. in electrical and computer engineering from Purdue University. (He is currently a postdoctoral researcher at the University of California, Los Angeles.) Qiu’s research focuses on novel low-dimensional materials for advanced electronics and quantum applications. His current interest includes employing topological materials for topological quantum computing.

Qianwen Wang is an incoming assistant professor of computer science and engineering. She received her bachelor’s from Xi’an Jiao Tong University and her Ph.D. from Hong Kong University of Science and Technology. Prior to Minnesota, Wang served as a post-doctoral researcher at Harvard University in the Department of Biomedical Informatics. As a visualization researcher, she created interactive visualization tools that enable humans to better interpret AI and generate insights from their data.

Katie (Yang) Zhao is an incoming assistant professor of electrical and computer engineering. Her research interest resides in the intersection between Domain-Specific Acceleration Chip and Computer Architecture. In particular, her work centers around enabling AI-powered intelligent functionalities on resource-constrained edge devices. Zhao received her bachelor’s and master’s from Fudan University, China, and Ph.D. from Rice University. (She is currently a postdoctoral researcher at Georgia Institute of Technology.)

Learn more about our goal to hire 60 new faculty in three years at the CSE recruiting website .

If you’d like to support faculty research in the University of Minnesota College of Science and Engineering, visit our CSE Giving website .

Join our winning team

Our unique combination of science and engineering within one college in a vibrant, metropolitan area means more opportunities for you. Learn about faculty openings.