AI, visualization, and models for complex systems.

We build computational methods that help researchers see structure, reason about change, and make uncertainty visible across healthcare, engineering, and science.

Explore research themes Read the research

Research themes

Three ways into the lab

Start with the kind of system you want to understand. Follow a theme into projects, visuals, and the papers that support the work.

Posterior-aware motor states connect clinical assessments to imaging-associated validation.

Posterior motor states connected to clinical assessments, patient-level phenotypes, DaTSCAN, and MRI validation — Posterior-aware motor states connect clinical assessments to imaging-associated validation.

01We infer the unseen

Healthcare AI

Interpretable models for multimodal health data, patient heterogeneity, and longitudinal disease monitoring.

ImagingBiomarkersClinical data

Evidence & tools

Go from a theme to the work behind it.

Short project overviews provide the map. Publications, software, and the full project index provide the technical depth.

About the Center

The Computational Visualization Center is a cross-disciplinary research group at the University of Texas at Austin, developing core technologies for computational modeling, simulation, analysis, and visualization of natural and synthetic phenomena. Under the joint auspices of the Oden Institute and the Department of Computer Science, our work spans machine learning, geometric modeling, scientific computing, and biomedical applications.

Computational Visualization Center group

Our Team

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Chandrajit Bajaj
Director, Principal Investigator
Ryan Farell
Researcher
Yi Wang
PhD Candidate
Luke McLennan
PhD Student
Shubham Bhardwaj
PhD Student
Omatharv Bharat Vaidya
Graduate Student
Ashwin Vinod
Graduate Student
Garvit Bansal
PhD Student
Trung Nguyen
Graduate Student
Thribhuvan Rapolu
Graduate Student
Harsh Tirhekar
Graduate Student
Aditya Sai
Graduate Student