University of Texas at Austin


Computational Medicine – A Campus Wide Collaboration

By John Holden

Published Feb. 10, 2022

Computational Medicine research gets major boost through the launch of a dedicated Graduate Portfolio Program.

A new Graduate Portfolio in Computational Medicine combines novel and existing courses from across the University of Texas at Austin to create a unique program in a rapidly expanding medical field.

“The practicing physician of the future needs to be able to understand how to think about data: how to visualize, interpret and accurately predict patient outcomes.” 

  - Dr. David Paydarfar, Dell Medical School

Computational Medicine is an emerging discipline that uses physics-based and data-driven advanced mathematical approaches to model complex human systems along a spectrum of scales. Models can be built at the cellular level, the organ level of the human body, or even for an entire health care system.

Models are developed using a combination of theory, knowledge and data-driven approaches allowing for the design of detailed simulations as multilayered and complex as the human body itself. They are dynamic entities that can be improved and built upon as new research emerges and reshapes established wisdom.

At its core, Computational Medicine aims to capture the individuality of health and disease for accurate decision making at all levels - from patient to policy.

UT Austin had, heretofore, lacked a formal training program at the interface of mathematics, computation and medicine, despite its strengths in all three individual fields. 

Now, a new Graduate Portfolio in Computational Medicine will be offered for the first time in Fall 2022. Enrolled graduate students will be able to obtain credentials in cross-disciplinary areas of Computational Medicine during their masters or doctoral degree. The Portfolio is highly interdisciplinary in nature with participation from 17 different units across campus.

While the majority of courses that make up the Portfolio are already available at UT Austin, they had not been consolidated to create a cohesive and comprehensive program.

Easier said than done. Given its interdisciplinary nature, over 100 signatures of approval were required from participating stakeholders. Expertise from the Cockrell School of Engineering, College of Natural Sciences, Dell Medical School, the Department of Psychology, College of Pharmacy, Computer Science and the Oden Institute for Computational Engineering and Sciences are now working together.       

Oden Institute director, Karen Willcox, is delighted to see this Graduate Portfolio come to fruition. “I’m personally very excited because this Program not only further cements our burgeoning partnership with Dell Medical School, but getting approval from so many stakeholders at UT Austin speaks to how this new course touches so many parts of campus.” 


Historically the pipeline into Computational Medicine has primarily come from the Oden Institute’s Computational Science, Engineering and Mathematics (CSEM) program. The Institute trains students in advanced scientific computing, many of whom arrive with strong mathematical and physical science backgrounds, but few come with any prior knowledge of biology or medicine. 

“This limits their ability to participate in, and contribute to, a growing field of enormous future potential and importance,” said Thomas J.R. Hughes of the Oden Institute, one of the Portfolio’s principal architects.

“Our aim is to provide a vehicle for students to pursue a program of study that will prepare them to interact knowledgably and collaborate productively with members of the medical community on interdisciplinary, cutting-edge research,” said Hughes. 

Students have also entered the field of Computational Medicine through the Departments of Biomedical Engineering (BME), Mechanical Engineering (ME), and Aerospace Engineering and Engineering Mechanics (ASE/EM) at the Cockrell School. There is significant interest from the Department of Electrical and Computer Engineering (ECE) as well.

“The proposed Graduate Portfolio in Computational Medicine is a top priority to Electrical and Computer Engineering (ECE) students in the BioECE track, which is the third-largest graduate track in ECE,” said Jon Tamir, Assistant Professor in ECE, and an instructor of one of the portfolios General Topics courses.

“In particular, faculty and students in this area integrate biological and medical domain expertise in a variety of ways, from low-level medical system design to full clinical assessment protocols.”

This work requires a multidisciplinary approach because practitioners interface with scientists, engineers, clinicians, and human subjects with different backgrounds.

“The proposed Graduate Portfolio offers these students rigorous focus areas within Computational Medicine to build this domain expertise and specialize it for their career interests and goals,” added Tamir.


Course Outline

Students will be introduced to the concept of the human body as a system that can be understood in mathematical terms.  This is likely to be an entirely novel way of viewing human physiology, but it underpins the computational approach to medicine. “More and more medical outcomes are being cast in mathematical frameworks,” said Dr. David Paydarfar from Dell Medical School. Paydarfar is another chief architect of the Portfolio and co-designer of one of its new courses: Mathematical Physiology.

“You might have a doctorate in medicine, but if you don’t have the tools to understand data and the mathematical frameworks being developed to interpret it, medicine as a profession will become increasingly ineffective.”

The second central component is medical imaging - one of the most far-ranging and flexible methods of analysis available for quantitative study of the human body in both the pre-clinical and clinical settings.

“Modeling and analysis in virtually all areas of Computational Medicine begins with medical imaging,” said Hughes. “Its profound place in the subject is akin to the telescope in astronomy or the microscope in biology.”

Undergraduate courses in Human Systems Physiology, Quantitative Engineering Physiology, and Normal Body Structure and Function are recommended for students with no prior coursework in biology or medicine to strengthen their backgrounds before starting the Portfolio program.

Medical Specialization

Medicine is an enormous field consisting of numerous subdisciplines. Computational medicine at UT Austin is a global leader in research in a number of crucial specialized areas, so naturally the Portfolio puts an emphasis on education and training in areas that play to our strengths.

The new Portfolio aims to offer courses that will be of fundamental benefit to students who wish to pursue a career in Computational Medicine, while at the same time providing options to suit students whose interests reside within other specific medical subdisciplines. 

In particular, three areas of specialization have been identified: cardiology, oncology and neurology. UT Austin is already doing extensive research in each with rich, collaborative networks already in place across campus. The Portfolio has been designed to offer coherent programs of courses, not only in these three focus areas, but with the flexibility to allow for the design of other specialized areas as the University of Texas at Austin continues establishing itself as a world leader in Computational Medicine.   

“It’s very important that we have a program that's dedicated to the mathematical, computational foundations of medicine at UT Austin,” said Paydarfar. “Not only are we very well positioned to do so, but it is a critical area for the future of medicine.” 

Working with many people across UT Austin, Thomas J.R. Hughes, Professor of Aerospace Engineering and Engineering Mechanics, and Dr. Radek Bukowski, M.D., Dell Medical School – Women’s Health, led the Working Group on the three-year effort to make the Graduate Portfolio in Computational Medicine a reality. 

Other members of the Working Group are Todd Arbogast, Professor of Mathematics and Chair of the Graduate Studies Committee (GSC) for Computational Science Engineering and Math (CSEM); J. Tinsley Oden, Professor of Aerospace Engineering and Engineering Mechanics and founding Director of the Oden Institute; David Paydarfar, M.D., Professor, Dell Medical School - Department of Neurology; Paul Rathouz, M.D., Professor,  Dell Medical School - Population Health; Michael Sacks, Professor of Biomedical Engineering; and Thomas Yankeelov, Professor of Biomedical Engineering.

Moving forward, the Working Group members will transition to become the Program Steering Committee, which will provide oversight of the Portfolio program.  Michael Sacks, Professor of Biomedical Engineering and Director of the Oden Institute’s Willerson Center for Cardiovascular Modeling and Simulation will be the inaugural Program Chair.    

For more information, please contact Stephanie Rodriguez, Oden Institute Graduate Program Coordinator.