Willcox Research Group
From Data to Decisions in Complex Systems
The Willcox Research Group is developing scalable computational methods for design of next-generation engineered systems. The group has a particular focus on scientific machine learning and model reduction as a way to learn principled approximations from data, and on multifidelity formulations to leverage multiple sources of uncertain information.
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Directors
Karen E. Willcox
Faculty and Research Staff
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Staff
News in brief
News
April 9, 2026
Oden Institute Announces Inaugural Kay Bailey Hutchison Computational Energy Fellows
Two fellows were selected for the new Kay Bailey Hutchison Energy Fellowship, a collaboration between the Oden Institute and the KBH Energy Center. Fellows will focus on nuclear systems and digital twins, using simulation and machine learning to improve energy infrastructure, forecasting, and decision-making.
News
Feb. 27, 2026
After a Decade of Pioneering Digital Twin Research, UT Emerges as a Global Leader in AI for Science
After more than a decade of advances in AI, mathematics and supercomputing, UT is shaping the future of digital twins — bringing together researchers across campus to deploy physics‑informed, AI‑powered models for energy, healthcare, national security and natural hazard mitigation.
News
July 7, 2025
90,000x Faster: Breakthrough Cuts Rocket Engine Simulations from Days to Seconds
A research team led by UT Austin has achieved a 90,000x speedup in simulating next-generation rotating detonation rocket engines, dramatically reducing computation time. This breakthrough enables real-time engine design and optimization.