carnegie mellon university phd thesis

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Thesis & Dissertation Deposit

As per Carnegie Mellon’s  Student Handbook , most graduate students are required to submit copies of their theses and dissertations to the University Libraries.  The Libraries maintains  KiltHub , a free, open access repository of CMU research, and provides access to and assistance with  ProQuest Dissertations & Theses , a commercial repository and database of dissertations from institutions around the world. Learn more in the Theses and Dissertations research guide .

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Ph.D. program

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The Doctor of Philosophy (Ph.D.) degree is the highest academic degree awarded by any university. Students pursuing a Ph.D. in chemical engineering become independent researchers equipped to apply chemical engineering principles and advanced analytical and experimental techniques to solve open-ended research problems. The education and training prepare students for careers in academia, industry, and government research.

Ph.D. candidates

The Ph.D. program is for students who want to direct their own comprehensive research project and receive the ultimate license for a career in research in industrial, academic, or government laboratories. The Ph.D. requires four to five years of work to acquire knowledge, form a plan, do the work, persist through the ups and downs of confronting the unknown, and learn to communicate the results.

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• Ph.D. student handbook

Our Ph.D. graduates join an elite global scientific and technological club whose members have both the privilege and responsibility to peer into the future and help shape it. The Ph.D. program in chemical engineering at Carnegie Mellon also is a living space where students meet and form lifelong bonds with like-minded peers within their research group and across the program. Our program features a strong graduate student association that provides an instant welcoming community.

Ph.D. thesis

The cornerstone of a Ph.D. education is a research-based thesis. First, candidates select a research area and choose a faculty mentor called a thesis advisor. The advisor then guides the student as they develop a plan of investigation to advance the state-of-the-art in the selected research area.

By the end of the student’s thesis research, the student must have assembled an expert’s level of knowledge in the topic area and must demonstrate the ability to conduct an independent investigation. At that point, the student summarizes the knowledge generated through their research program in a doctoral thesis and presents the results to the public in an oral thesis defense. The knowledge generated is disseminated to the scientific and technological community by publishing articles in the scientific literature and through presentations at scientific and technological meetings and symposia.

During the program, candidates form a plan, execute the plan, and communicate the findings alongside peers at the highest academic level.

Program cost

All full-time Ph.D. students accepted through the normal application process receive fellowships that pay tuition, fees, and a stipend for living expenses for up to five years, as long as sufficient progress is being made toward degree completion. These awards are enough to cover all costs for the year (including summers). Students are required to pay for books and course supplies. Off-campus housing is available within walking distance of campus.

Admissions requirements

Admission decisions are based on overall academic performance, recommendation letters, and standardized test scores, if applicable. Prospective students must have completed a regular four-year undergraduate course in chemical engineering or a related discipline at a recognized university with better than a “B” average in chemical engineering courses and overall.

Learn more about the Ph.D. program’s admissions process and apply!

Have questions about our admissions process or Ph.D. program? Visit our  FAQ page .

Pursue a Ph.D. degree in chemical engineering from Carnegie Mellon University

Doctoral Degree in Computer Science

Carnegie Mellon's Ph.D. in Computer Science is, above all, a research degree. When the faculty award a Ph.D., they certify that the student has a broad foundation and awareness of core concepts in computer science, has advanced the field by performing significant original research and has reported that work in a scholarly fashion.

When you begin our Ph.D. program, you’ll take the Introductory Course for Doctoral Students — an intense two week program that orients you to the department, introduces you to research and education topics our faculty are interested in, helps you find a faculty advisor and familiarizes you with Carnegie Mellon’s resources. Next, you’ll gain a broad understanding of fundamental research issues in major areas of computer science through coursework and original research. Finally, you’ll write and orally defend a thesis that guarantees you understand the area well enough to advance the state of knowledge in the field.

During the first two years of the program, you’ll gain the foundation of knowledge that will allow you to become an expert researcher in computer science, primarily by

Mastering a body of graduate material, achieved by passing 96 university units worth of graduate courses (equivalent to eight full-time courses).

Learning how to organize and begin to carry out original research, achieved by participating in directed research.

You will also serve as a teaching assistant, hone your writing and speaking skills and maintain your programming prowess. You’ll also receive periodic evaluation of your progress, and must make satisfactory progress to continue in the program.

Time Commitment:

As a Ph.D. student in computer science at CMU, you'll spend roughly five years acquiring a body of technical knowledge that includes a familiarity with the breadth of the field, as well as a deep understanding of your research area. From your second month in the program, you'll work closely with your faculty advisor, who is charged with guiding your education and monitoring your progress through the program. You'll take courses, teach and perform directed research — all to ensure that you leave Carnegie Mellon as an expert in your field. For a complete breakdown of our program requirements, read our Ph.D. Handbook .

Financial Information:

The Computer Science Department offers all Ph.D. students full financial support while they are in good academic standing in their respective programs. To learn more about Ph.D. funding, visit the SCS  Doctoral Programs  webpage.

Graduate Tuition: https://www.cmu.edu/sfs/tuition/graduate/scs.html

Student Fees: https://www.cmu.edu/sfs/tuition/fees/index.html

Carnegie Mellon Graduate Student Financial Aid: https://www.cmu.edu/sfs/financial-aid/graduate/index.html

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Machine Learning - CMU

Requirements for the phd in machine learning.

• Completion of required courses , (6 Core Courses + 1 Elective)
• Mastery of proficiencies in Teaching and Presentation skills.
• Successful defense of a Ph.D. thesis.

Teaching Ph.D. students are required to serve as Teaching Assistants for two semesters in Machine Learning courses (10-xxx), beginning in their second year. This fulfills their Teaching Skills requirement.

Conference Presentation Skills During their second or third year, Ph.D. students must give a talk at least 30 minutes long, and invite members of the Speaking Skills committee to attend and evaluate it.

Research It is expected that all Ph.D. students engage in active research from their first semester. Moreover, advisor selection occurs in the first month of entering the Ph.D. program, with the option to change at a later time. Roughly half of a student's time should be allocated to research and lab work, and half to courses until these are completed.

Master of Science in Machine Learning Research - along the way to your PhD Degree.

Other Requirements In addition, students must follow all university policies and procedures .

Rules for the MLD PhD Thesis Committee (applicable to all ML PhDs): The committee should be assembled by the student and their advisor, and approved by the PhD Program Director(s).  It must include:

• At least one MLD Core Faculty member
• At least one additional MLD Core or Affiliated Faculty member
• At least one External Member, usually meaning external to CMU
• A total of at least four members, including the advisor who is the committee chair

Joint Carnegie Mellon-University of Pittsburgh Ph.D. Program in Computational Biology

Eligibility.

• Am I am eligible for the program? Judgments about the suitability/eligibility of candidates for the program are made by the Admissions Committee. No assessment of candidate qualifications can be made prior to admissions decisions. Recommended courses are listed   here.
• Is a previous research background in a bioinformatics-related field necessary for successful enrollment? No. Previous research and associated publications are often considered favorably by the Admissions Committee. However, these are not requirements.
• Am I eligible for the program if I do not have any professional computer skills? In addition to computer science, we admit students from physical sciences, biological sciences, mathematics, statistics and engineering, who may not have professional computer skills. If necessary we may recommend you to take extra coursework in Programming, Fundamental Data Structures, or Algorithms.
• I am intending to take a course in one of the programming languages (Java, C++ etc.), but the course will not be completed at the time I wish to apply. Will the course still help to make my application strong? You can include a list of courses that you are currently taking or planning to take with your application for consideration by the Admissions Committee.
• Will a prior MS in bioinformatics or computational biology have a great impact on my admission to the joint PhD program? No. We consider each application separately on the basis of many criteria, including research statement, undergraduate (and if applicable graduate) coursework performance, GRE scores, letters of recommendations, etc. The fraction of our current students who have an MS degree in bioinformatics or computational biology is only 16%. Although about 35% of our current students had a prior MS when they entered our program, such students were admitted because they had good research experience.
• Will the program continue to consider applications after the deadline? If so, when are the last dates? Under special circumstances, applications submitted after the deadline may be considered. If you would like to request special permission to submit a late application, please contact one of the program directors.

Institutional/Department Codes

What Institutional/Department codes should I use for score reporting? For TOEFL, use Institution code 4256, Department code 78.

TOEFL Scores

• What are the TOEFL requirements for international students? If your native language is not English, then you must submit the   Test of English as a Foreign Language   (TOEFL). All students need to submit a TOEFL.  No exceptions . A minimum score of 250 (600 paper, 100 iBT) on the computer TOEFL or a minimum of 7.0 on the IELTS is required for admission to the program. Scores must be less than two years old.

If you are currently working on or have received a bachelor’s and/or a master’s degree in the U.S. and your native language is not English, the TOEFL is still required . However, you may submit an expired test score up to five years old.

Do you accept IELTS score or Duolingoscore instead of TOEFL? Yes.   A minimum of 7.0 on the IELTS, and a minimum of 120 Duolingo score  is required for admission to the program.  We prefer that you take the TOEFL, but we will accept the  International English Language Testing System  (IELTS). The same restrictions of expiration dates apply with an IELTS. Please understand that equitable review of all applicants depends on having comparable sets of data in their applications.  We therefore strongly encourage all applicants to provide TOEFL or IELTS scores.  However, we understand that in some cases that it may not be possible for an applicant to test for TOEFL or IELTS.  If you are not a native English speaker, and despite your best efforts are unable to test for TOEFL or IELTS, you may take the Duolingo English proficiency test.

Financial Aid

• What financial aid is available should I be admitted in the program? All enrolled students receive full financial support, consisting of full tuition and stipend. The annual stipend for 2022-2023 is $33,360 (Pitt) or $38,400 (CMU).
• Is it necessary for me to apply for financial aid? No, your application to the program is considered to be an application for financial aid as well.
• What is the approximate overall cost of graduate study per academic year? The overall cost includes tuition and fees plus living expenses. Tuition and most fees are covered by the program, and a stipend is provided to cover your living expenses. The stipend has been set to provide a competitive level of support for our students. Pittsburgh’s cost of living is lower than similar metro areas and is 30 percent below the national average. This   CNN Cost of Living Calculator   can help you compare.

Research Projects

• What are the specific areas in which projects will be available? The best way to see what research projects are available is to look at the websites of our training faculty. Upon admission you will participate in our annual off-site retreat, at the end of orientation week, during which you will have the opportunity to interact with faculty members and learn about their research projects.
• The program website says to “read about the research interests of the training faculty and identify at least three faculty with whom you would be interested in doing thesis research.” Do I need to/may I approach and contact individual professors? You are welcome to approach and contact individual professors, if you’d like more information about their research interests. However, you are not required to contact them. Since admissions decisions are made by the Admissions Committee, faculty cannot make prior commitments to accept particular students.

Prerequisites

• I have not taken any undergraduate or graduate course on computational biology. Will it be viewed as a weakness in my application package? No. Students are evaluated based on many criteria, especially their academic excellence and potential. Computer science, physical science, mathematics or statistics courses are  recommended.  However, complementary/remedial courses will be made available to enrolled students who lack sufficient background in an area.

Core Courses and Electives

• Can I get credit for core courses or electives based on past graduate courses taken at other universities? Decisions on courses to be taken by each student are made by the Advising Committee after enrollment. That committee reviews prior coursework and can waive specific core requirements. Elective requirements are not waived.

Duration of the Program

• What is the duration of the program? Students are expected to complete their degree in 4 to 6 years. This time depends primarily on the research accomplishments of the student.

International Students

• When entering the program, who can help me with the immigration process? For students accepted through the University of Pittsburgh, contact the  Office of International Services.

Transfers to the Program

• My current advisor will be leaving academia and asked me to contact other faculty to see if they will be my future Ph.D. advisor. Can I transfer to your Ph.D. program? Requests for transfers are only considered along with applications for regular admission, according to the normal application cycle.

Electrical and Computer Engineering

College of engineering.

Kar and Parno Receive Professorships

• kristab(through)cmu.edu

The College of Engineering has announced the most recent faculty members to receive a professorship. As the highest academic award a university can bestow on a faculty member, professorships are reserved for those who show continued contributions in their field.

Professorships are established to support a particular faculty member or a field of research, both of which are critical to maintaining world-class quality education and research. Contributions help faculty members pursue a specific field of study, provide funding for graduate student involvement, purchase equipment, or travel to share their research.

With the approval of Provost Garrett, Soummya Kar has been named the Buhl Professor of Electrical and Computer Engineering, and Bryan Parno has been named the Kavcic-Moura Professor of Electrical and Computer Engineering.

Kar’s research interests include decision-making in large-scale networked systems, stochastic systems, multi-agent systems and data science, with applications in cyber-physical systems and smart energy systems. Kar is a Fellow of the IEEE, and, among other honors, with former ECE Ph.D. student Sérgio Pequito and University of Pennsylvania professor George J. Pappas won the 2016 O. Hugo Schuck Best Paper Award from the American Automatic Control Council in the Theory Category.

Parno’s research is primarily focused on investigating long-term, fundamental improvements in how to design and build secure systems. He formalized and worked to optimize verifiable computation, receiving a Best Paper Award (and later a Test-of-Time Award)at the IEEE Symposium on Security and Privacy for his advances. He coauthored a book on Bootstrapping Trust in Modern Computers, and his work in that area has been incorporated into the latest security enhancements in Intel CPUs.

The campus community will celebrate these honors at a formal ceremony in the coming months.

Related Faculty

• Soummya Kar
• Bryan Parno

Bachelor's Programs

Each year, the School of Computer Science admits students to undergraduate programs ranging from a traditional B.S. in computer science to a bachelor of computer science and arts. 

Whatever option you choose, you’re guaranteed to find a rigorous program dedicated to the real-world training and practical problem solving that has been the hallmark of computer science education at CMU since its inception.

B.S. in Computer Science

Carnegie Mellon's undergraduate major in computer science combines a solid core of computer science courses with the ability to gain substantial depth in another area through a required minor in a second subject. The curriculum also gives you numerous choices for science and humanities courses. Computing is a discipline with strong links to many fields, and our program gives you unparalleled flexibility to pursue these fields. Our mathematics and probability component ensures that you'll have the formal tools to remain current as technologies and systems change, but at the same time you'll gain insight into the practical issues of building and maintaining systems by participating in intensive project-oriented courses.

Unlike other universities, where research rarely occurs at the undergraduate level, CMU CS students often have part-time or summer jobs — or receive independent study credit — working on research while pursuing their bachelor's degree. If you're interested in a research/graduate school career, we offer an intensive course of research, equivalent to four classroom courses, culminating in the preparation of a senior research honors thesis.

Requirements

Current Computer Science Undergraduate Curriculum  

Computer Science Undergraduate curriculum information for prior years are available on the Previous Course Catalogs webpage .

How to Apply

Bachelor of Science in Music and Technology

Carnegie Mellon University's Music and Technology program was established in 2009 as a joint project between three of the schools: The School of Music, School of Computer Science, and the Department of Electrical and Computer Engineering. Information regarding this degree is available on the Bachelor of Science in Music and Technology website . 

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Home News CMU-Q grad places first in Pitt Three Minute Thesis competition

CMU-Q grad places first in Pitt Three Minute Thesis competition

Carnegie Mellon University in Qatar (CMU-Q) graduate Maher Khan won the Three Minute Thesis (3MT) competition at University of Pittsburgh’s School of Computing and Information where he is completing his PhD. 

Khan received dual degrees from CMU in computer science and information systems in 2017 . 

The Three Minute Thesis competition challenges doctoral students from around the world to present their theses in less than three minutes through speech and one static presentation slide. The competition challenges students to present their research in a compelling, accessible way.

Khan’s research is in intrusion tolerance in distributed systems. 

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Latest news, students turn to 3d printing solutions to improve sustainability, entrepreneurship course sparks idea for global health solution, bio sci student publishes meta-analysis in frontiers of immunology.

Chemistry: Theses and Dissertations

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About Theses and Dissertations

A dissertation or thesis is a document submitted in support of candidature for a degree or professional qualification presenting the author's research and findings.  (International Standard ISO 7144: Documentation — Presentation of theses and similar documents ).

For most universities in the U.S., dissertation is the term for the required submission for the PhD, and thesis refers only to the master's degree requirement.

Carnegie Mellon University

Carnegie Mellon theses are now ONLINE and can be searched through the ProQuest database Dissertations & Theses @ Carnegie Mellon University that enables access to citations and abstracts of all dissertations and theses, as well as the full text in PDF format.  Scroll down and select Dissertations & Theses, then do a regular search. Print versions are also available in the libraries' collection.

PRIMO ,  the Carnegie Mellon Library catalog, uses the term THESIS to denote both masters' theses and dissertations.  However, the number of master's theses is limited.  Within the libraries, theses are located in designated areas and are shelved in alphabetical order by the author's last name.  The catalog treats theses and dissertations like books, and they can be borrowed as such. Theses may be in print, microfiche, or microform.

• In catalog use the Advanced Search :  search by author, title, or keyword limiting to type THESIS.
• For a list of theses from a specific department, use Advanced Search to combine a keyword search for the name of the department with location THESES.  E.g., search for "Dept. of Computer Science" with THESES as the location.
• For a complete list of theses at Carnegie Mellon, use Advanced Search to search Carnegie Mellon University Dissertations in the Subject line.  

Other Universities

T he best source to find theses is ProQuest Dissertations & Thesis Global .  Policies regarding theses and dissertation collections largely vary between universities.  So check the library website of the university of interest.

Other Countries

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

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Neuroscience Institute

Not just neighbors, together, pitt and carnegie mellon train tommorow's biomedical engineers.

By Michael Aubele

& Andrew Doerfler

Joshua Tashman couldn’t divorce himself from his passion for engineering as he explored medical schools nearly a decade ago. So, he decided there was only one way to round out his formal education: He’d marry medicine and materials science.

That choice led him to Pittsburgh, where the University of Pittsburgh School of Medicine and Carnegie Mellon University run the Medical Scientist Training Program (MSTP), through which he earned his PhD in bioengineering in 2021 from Carnegie Mellon and his MD from Pitt in 2022.

“The real benefit here is that they’re different schools with different expertise,” says Tashman, grateful that he had the chance to learn from and train under brilliant faculty at both universities.

The universities share broad research interests and overlapping expertise in several fields—think neuroscience, robotics and bioengineering—and partner in programs beyond the MSTP.

Carnegie Mellon graduate student Kendra Noneman has a Pitt faculty advisor through the Center for the Neural Basis of Cognition, where researchers at both universities investigate the cognitive and neural mechanisms that give rise to biological intelligence and behavior. Working with J. Patrick Mayo, a PhD assistant professor of ophthalmology, gives her a chance to see clinical research firsthand as she studies where animals are looking based on neurons in the cerebral cortex.

Emily Lopez, another Carnegie Mellon student co-advised by Mayo, was excited that the partnership with Pitt connected her with a broader neuroscience community in Pittsburgh.

“It just increases the amount of and types of research I am exposed to and the people I can meet, which makes for a richer graduate student experience,” says Lopez, whose optogenetics research is part of a collaboration between Mayo and her Carnegie Mellon advisor, Matt Smith, a professor of biomedical engineering and codirector of the Center for the Neural Basis of Cognition. “In all honesty, I tend to lose track of which professors and students are from Pitt and which are from CMU; we are often mixed together at various events and even within labs.”

Together, the two universities are nurturing the next generation of biomedical leaders as their faculty pursue life-changing research.

“I think that over the years, the two universities have collaborated effectively to attract the best students to the city because of their complementary research strengths,” says Saleem Khan, PhD associate dean for graduate studies and academic affairs and professor of microbiology and molecular genetics in Pitt’s School of Medicine. “This is a great thing, because it helps both universities attract and recruit faculty and expands the breadth of their research.”

He says it also gives faculty bargaining power in attracting grant funding. Today, research projects at the School of Medicine involve collaborators from Carnegie Mellon more than any other institution outside of Pitt. In fiscal year 2023, their collaborations included 65 principal investigators and spanned 48 awards with a total worth of over $15.8 million.

Theresa Mayer, vice president for research at Carnegie Mellon, notes that, overall, “the University of Pittsburgh is by far and away CMU’s most frequent and deepest partner in research. Research at CMU is supported from funding awarded in partnership with the University of Pittsburgh more often than through any other source, outside of direct funding awards from major federal agencies like the National Science Foundation and the U.S. Department of Defense.”

And of course, Pitt and Carnegie Mellon share a neighborhood. Many faculty say they can’t immediately name another instance of having one of the country’s best medical schools sitting a few blocks from a top computer science school. In the Boston area, you’ll find a close case in Harvard Medical School and MIT. Yet those schools sit roughly two miles apart.

James Faeder, a PhD Pitt Med associate professor of computational and systems biology and Pitt’s program director for the joint Carnegie Mellon–University of Pittsburgh PhD Program in Computational Biology (CPCB), says there are intangible benefits to Pitt and Carnegie Mellon’s proximity, as well. Faculty from the two universities don’t just work in the same neighborhood, they often live in the same neighborhoods and socialize outside the lab. And on the student side, he points to the pride they take in their joint education:

“Our students view themselves as alumni of both schools.”

The serendipitous geography has made it easy to forge alliances that maximize complementary strengths in medical research. Dozens of Pitt students as well as dozens of Carnegie Mellon students are enrolled in formal programs between the universities.

Examples include the aforementioned MSTP and CPCB programs; the Molecular Biophysics and Structural Biology graduate program, where students can pursue research in disciplines ranging from cellular biophysics to virus structure and nanomachinery; plus the Program in Neural Computation, where computationally minded students can move seamlessly among neuroscience labs at both universities. And there are more informal collaborations than you can shake a pierogi at.

“This is a special part of the Pittsburgh community,” says Douglas Weber, a PhD and the Akhtar and Bhutta Professor in mechanical engineering and neuroscience at Carnegie Mellon. “There are elite institutions that are unable to collaborate between departments. But we’re able to do that here across institutions.”

An emerging generation of physicians and scientists has taken advantage of this city’s extraordinary academic offerings to enrich health care—not only in Pittsburgh, but well beyond. What follows are stories from three of these investigators.

Joshua Tashman’s (right) work on 3D-printed organs has spanned projects with Carnegie Mellon bioengineers and Pitt’s Cary Boyd-Shiwarski (left). (Aimee Obidzinski/University of Pittsburgh)

When Joshua Tashman tells you what he accomplished as part of a research team at Carnegie Mellon, you can understand bioengineering’s appeal to him, especially after he tells you a little about himself.

The self-professed tinkerer used 3D bioprinting to engineer models of the human heart—including one that pumped for weeks.

Tashman, who earned a bachelor’s in mechanical engineering from Cornell University, played an integral role on the Carnegie Mellon team that 3D-bioprinted a functioning tubular heart that is similar to one in embryonic development. They took cardiomyocytes and cardiac fibroblasts—the cells that make up the heart muscle and the ones that produce connective tissue, respectively—that were derived from stem cells and printed them in a tube made from collagen. The tube spontaneously began contracting within a few days of construction and pumped for roughly a month.

Tashman’s most recent work in Pittsburgh was in Pitt Med’s Division of Renal-Electrolyte under the direction of Cary Boyd-Shiwarski (MD ’12, Res ’14, Fel ’16), an assistant professor of medicine. There he investigated how potassium depletion can lead to kidney injury.

Before he headed to Boston over the summer for a Mass General Brigham Combined Residency in pathology, Tashman explained that cell culture generally is two-dimensional, so it has limitations: The lab-grown cells aren’t exposed to the same environment that they are in the body.

“They’re exposed to a mechanical environment and a flow environment that is specific to the geometry and physiology in the human body,” he says of kidney cells. “These cells line a tube in the body with a flow [of water and solutes] passing over them. And these things are very important for the kidney cells to think that they’re in a kidney and that they should behave like kidney cells.”

So, when running experiments on how potassium levels affect the creation and excretion of ammonia, the most common lab model doesn’t reproduce many of the same biomarkers found in the kidney.  “The idea then is, can we 3D print something that allows us to recreate the mechanical and chemical cues?”

Tashman collaborated with Daniel Shiwarski, a PhD and Pitt assistant professor of bioengineering and medicine who also studied at Carnegie Mellon (and is married to Boyd-Shiwarski), to focus on engineering the system as closely as possible so that proximal tubule cells grow on it.

Tashman had teamed up with Daniel Shiwarski before. It was while earning his PhD that he and Shiwarski worked in the group that constructed the heart models—that was in the lab of Adam Feinberg, the Arthur Hamerschlag Career Development Professor in the Departments of Biomedical Engineering and Materials Science and Engineering at Carnegie Mellon. The researchers made computer models of tissue and organs and recreated them with printed biological materials.

Feinberg encouraged the team to spread their newly acquired know-how to biomedical engineers everywhere, Tashman says. “He published open-source papers. So, he would let me make step-by-step guides, and we would give all the designs away so that other people could actually build everything that we designed.

“I’ve seen people on Twitter, for instance, post videos of things that I’ve helped design that they printed out and built themselves. That’s been pretty cool.”

Eric Strobl knew he wanted to use big data to find new treatments. (Erin O. Smith/Vanderbilt University Medical Center)

Big data, big opportunities 

Eric Strobl (PhD ’17, MD ’19) remembers reading about the human brain in high school and thinking it was the most interesting subject he’d ever encountered. He knew he wanted to study it. But as he got to college, he found himself wondering what he would do with all the knowledge he was accumulating.

Computer science and biomedical informatics gave him an answer. Strobl liked the idea that he could contribute to medical knowledge—and maybe even identify new treatments—by mining big datasets; the approach helps researchers find answers more quickly and economically than clinical trials would.  “I was not convinced that the phrase, ‘Correlation does not imply causation,’ was the end of the story,” he says. He wanted to see if stronger conclusions could be drawn from big data, particularly from large sample sizes.

Strobl went on to pursue his MD and PhD through the MSTP; he found himself pulled toward an area of study called causal discovery—a way of determining cause-and-effect relationships from big data. Researchers like Strobl’s advisor Shyam Visweswaran, an MD, PhD Pitt professor of biomedical informatics and a neurologist, develop algorithms to tease out causal connections waiting to be found in medical data like electronic health records—and use those takeaways to come up with new treatments.

As he got deeper into his research, Strobl’s ideas caught the attention of Peter Spirtes, a Carnegie Mellon philosophy professor and one of the originators of causal discovery.

“I was very skeptical of what he was saying, and it made me want to talk to him in more depth,” Spirtes says. “And he convinced me that he did know what he was doing.”

Strobl began collaborating with Spirtes and Kun Zhang, also of Carnegie Mellon’s philosophy department. Many faculty in that department look for ways to apply technical approaches in mathematics, statistics and computer science to big questions about knowledge.

Just as Pitt’s proximity to Carnegie Mellon allowed Strobl to work with some of the foremost experts in the theoretical side of causal discovery, Spirtes and Zhang appreciated the chance to work with those embedded in the world of patients and treatments.

“[Strobl] was really motivated by real problems,” says Zhang. “We’re working on the ideas and the methodologies. So his contribution was essential to our work.”

Strobl’s PhD dissertation would demonstrate new ways of thinking about feedback loops in causal discovery that combined approaches from both biology and computer science. Philosophy and physics treat feedback loops—where a system’s output either spurs on or hinders the system—as if two things caused each other simultaneously, which doesn’t reflect what’s happening in the body.

So Strobl developed a new algorithm that outperformed a commonly used one in its predictions. He also took into account the different stages of a disease that may be reflected in data from a sample. The dissertation won the Drs. S. Sutton Hamilton MSTP Scholar Award, recognizing Strobl’s contribution to scientific literature.  

Strobl also published papers that mathematically defined and identified root causes of disease from data with the goal of applying the methods to psychosis. Psychosis is complex—which lends itself well to Strobl’s approaches. They’re helpful in sorting through the manifold factors involved in a disease.

Strobl is now a psychiatry resident at Vanderbilt University Medical Center, but he won’t be away from Pitt for long. In July 2024, he’ll join Pitt’s faculty as an assistant professor of biomedical informatics with a secondary appointment in psychiatry. Visweswaran is excited that his onetime advisee will be the Department of Biomedical Informatics’ first faculty member with a clinical appointment, helping to apply their work to pressing, real-world problems. He also hopes Strobl’s arrival will mark the beginning of a renewed interest in causal inference at Pitt, which they expect to expand on with future hires.

Strobl’s research will use genomic data for causal inference to address autism and neurodevelopmental disorders. He’ll continue to work with Carnegie Mellon’s Spirtes and Zhang to fine-tune his algorithms. Pitt, he says, offers a collaborative community that brings together his different interests.

“It’s very rare to have a lot of expertise in both medicine and causal inference in the same place,” he says. “It’s also rare, I think, to have a combination of people who are interested in biology and clinical medicine. Usually, the communities are very separate.”

Janie French tapped into expertise at Carnegie Mellon for her dissertation on bacterial coinfection. (Aimee Obidzinski/University of Pittsburgh)

Coinfection collaboration

Janie French (PhD ’23) first became interested in microbiology after a harrowing spring break with her rowing team at the University of Wisconsin, Madison. On a training trip in Oak Ridge, Tennessee, the whole team came down with norovirus. Having no idea at first what was causing the collective gastrointestinal distress was the scariest part. “Knowing what we had was the first step to feeling better about it,” French says. (Thankfully, they made it back home and healthy after a few days of misery and a canceled race.)

The experience, along with an undergraduate class in virology, set her on the path toward a PhD in microbiology and immunology. French is now a medical science liaison for HeathTrackRx, a company that performs diagnostics for infectious diseases. As a graduate student, she worked in the lab of Seema Lakdawala, then a PhD assistant professor at Pitt who studies influenza A, which has been the culprit behind some of history’s worst pandemics and regular seasonal epidemics.

“When I was rotating [labs], I really liked the translational aspect of Seema’s work,” French says. Studying ways to mitigate transmission, “you didn’t have to search very hard to connect our work to improved health outcomes.” (Lakdawala has since moved to Emory University.)

French found herself interested in studying how the body battles two infections at once, with a project focused on coinfection of influenza virus with the bacteria Streptococcus pneumoniae. The latter, a major cause of bacterial pneumonia and other infections, has been known to worsen death rates during flu outbreaks, including the 2009 H1N1 pandemic. French wanted to understand more about how and why that happens.

“As a flu lab studying transmission, we wanted to know whether the pathogens truly were synergistic. And if they were, what exactly was going on there?” French says.

To learn whether and how these infections were collaborating to wreak havoc, French had to do some collaborating of her own. She turned to an expert on S. pneumoniae: N. Luisa Hiller, the Eberly Family Career Development Associate Professor of Biological Sciences at Carnegie Mellon. 

The team also included Pitt’s Valerie Le Sage, a PhD research assistant professor, and Lakdawala, as well as Karina Mueller Brown, a PhD who was a Carnegie Mellon graduate student at the time. Together, they looked at coinfection in ferrets, which are naturally susceptible to flu, have a respiratory tract more similar to humans than mice do, and cough and sneeze like humans.

As they reported in a paper published in 2022, they found in ferret models that getting the bacterial infection after the virus led to more severe symptoms. But, surprisingly, it didn’t increase transmission of the virus or the viral load—they actually found less virus in nasal washes of coinfected animals.

Why? One clue might be in mucus crusts the researchers noticed on the coinfected ferrets’ noses, not seen during flu or pneumonia infection alone. More study is needed, French says, but “it’s possible the virus is getting stuck in mucus deeper within the nasal passages.” It’s likely that coinfection prompts a heightened immune response.

In a paper published in 2023, they looked at aerosols expelled by coinfected ferrets through their coughs and sneezes. Surprisingly, says Hiller, it appears that when both pathogens are in the same released droplets, they can influence how long each persists outside the body.

The joint expertise was critical to the work—and Carnegie Mellon’s proximity to Pitt made it easy to exchange samples, get feedback and share equipment.

“We couldn’t have done the project without them,” says French.

“And from the starting experiments, it blossomed into additional questions we were interested in asking and future directions we could take.”

Says Hiller, “The right collaborations drive scientific discoveries.” 

Teaming up, getting results

Results of teamwork between biomedical researchers at Pitt and Carnegie Mellon often make headlines. In recent years, for instance, you might have learned about these breakthroughs:

Neuroscientists and physicians from the two universities showed that   children with just one brain hemisphere were able to perform surprisingly well on tasks typically associated with the opposite hemisphere.   Their work sheds new light on how the brain functions and develops by suggesting that for children, each brain hemisphere is plastic and capable of mimicking the other when necessary.

UPMC is stopping the spread of hospital infections with the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), machine-learning technology developed by Pitt clinicians, epidemiologists and Carnegie Mellon partners. The program couples genomic sequencing with algorithms connected to a vast trove of electronic health record data. When sequencing detects that two or more hospital patients have near-identical strains of an infection, the platform quickly mines those patients’ health records for commonalities; it then alerts infection preventionists to investigate and halt further transmission. In October 2022, EDS-HAT flagged a drug-resistant infection linked to eye drops. Months later, the Centers for Disease Control and Prevention (CDC) issued a warning about infections from certain eye drops.

Pitt physical medicine and rehabilitation experts are working with faculty at the Robotics Institute at Carnegie Mellon to add artificial intelligence to the neuroprosthetic system that has allowed paralyzed research participants to use a robotic arm that they control with their minds. In a triumphant 2016 demonstration of the technology, one man fist bumped former President Barack Obama. The Henry L. Hillman Foundation was among those providing funds for this research, which originated in Pitt’s neurobiology department.

And in an astonishingly promising turn for stroke research, scientists and surgeons from the universities found that   spinal implant technology (commonly used for pain) allows stroke patients to move and use paralyzed arms and hands.

We can expect more good news once Pitt’s BioForge, which will accelerate the manufacturing of living therapies, is built next to Carnegie Mellon’s own advanced manufacturing innovation facility in Hazelwood Green.   There, the universities will also be next-door neighbors.   —MA

Photography by Aimee Obidzinski/University of Pittsburgh and Erin O. Smith/Vanderbilt University Medical Center | Silhouettes by Frank Harris This story appeared in the Winter '23-'24 issue of Pitt Med Magazine. 

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