University of Texas at Austin

Cross-
Cutting
Research Area

Computational Medicine

Modeling the Individuality of Health and Disease for More Accurate Decision Making

A Patient-Centric Approach - Providing Diagnosis and Treatment Tailored to Each Individual

Through its advanced mathematical and simulation approaches, computational medicine can build models of human physiology with unprecedented accuracy - from the cellular level to the entire body.

An Overview: Computational Medicine

What is Computational Medicine?

Computational Medicine uses advanced mathematical and simulation approaches to model the human body in a spectrum ranging from the molecule to the organ to the entire body and ultimately, to the health care system. To accurately represent such complex systems, the models need to capture the individuality of health and disease for accurate decision making at all levels. Ranging from the patient to the policy, these require state-of-the-art computational capabilities to make them a reality. The models can be theory–, knowledge–, or data–driven, or any combination of the three.

Current research areas

Research is multifaceted, ranging from foundational advances in theory, methods and algorithms, to real-world impact in societal grand challenge problems.

medical imaging

Medical imaging

molecular biophysics

Molecular biophysics

cardiovascular-science

Cardiovascular Science

neuroscience

Neuroscience

oncology

Oncology

Genomic dataset analysis

Genomic dataset analysis

Computational Medicine Portfolio

Portfolio programs promote cross-disciplinary scholarship and study by bringing together faculty and students from a variety of disciplines whose interests transcend the boundaries of traditional academic departments. The Computational Medicine Portfolio will provide an opportunity for UT Austin graduate students to pursue a program of study that will prepare them to interact and collaborate with members of the medical community on interdisciplinary, cutting-edge research.

Working with partners

The University of Texas MD Anderson Cancer Center, Oden Institute’s Center for Computational Oncology, led by Dr. Tom Yankeelov, and TACC are working together to find new cancer treatments through integrating oncological data with mechanism-based modeling techniques. MD Anderson is one of the world's largest and most respected centers devoted exclusively to cancer patient care, research, education and prevention. Read more about our collaborations.

The Willerson Center for Cardiovascular Modeling and Simulation, led by Dr. Michael Sacks, at Oden Institute has been a long-standing partner of the Texas Heart institute (THI). The THI is recognized internationally for research programs in cardiology, cardiovascular surgery, regenerative medicine and pathology. The partnership with the Oden Institute is underpinned by research to advance computational modeling of the cardiovascular system with a view to providing tailored care for each individual patient suffering from heart disease — the number one cause of death worldwide.

Centers and Groups

To learn more about projects and people in Computational Medicine, explore the centers and groups with research activities in this cross-cutting research area.

Center for Computational Oncology

Willerson Center for Cardiovascular Modeling and Simulation

Center for Computational Life Sciences and Biology

Center for Computational Medicine

News in brief

Moncrief Internship Helps Student's Quest to Solve Inverse Problems

News

Jan. 20, 2026

Moncrief Internship Helps Student's Quest to Solve Inverse Problems

While most engineers predict effects from causes, undergraduate and two-time Moncrief Intern Arushi Sadam is flipping the script: developing innovative methods to infer causes from effects.  

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Three New Cancer Projects Receive Funding in Joint Collaboration Between Oden Institute, MD Anderson and TACC

News

Dec. 4, 2025

Three New Cancer Projects Receive Funding in Joint Collaboration Between Oden Institute, MD Anderson and TACC

The selected projects apply imaging, computational modeling, and digital twin technologies to improve prediction, treatment planning, and early detection across prostate, head and neck, and liver cancers.

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New Technology, Data Drive Advancements in Breast Cancer Care

Feature

Oct. 16, 2025

New Technology, Data Drive Advancements in Breast Cancer Care

UT Austin researchers, in partnership with MD Anderson and Dell Medical School, are advancing breast cancer care through predictive modeling, protein-based therapies, 3D reconstruction tools, and large-scale data resources. These innovations aim to make treatments more precise, accessible, and patient-centered.

Read more