Anirban Chaudhuri
Research Associate | Oden Institute for Computational Engineering & Sciences
I am a Research Associate at the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin. Prior to joining the Oden Institute in 2021, I spent six years as a postdoc and then Research Scientist at Massachusetts Institute of Technology. I worked with Prof. Karen Willcox in the Department of Aeronautics & Astronautics at MIT. I am a member of AIAA Non-Deterministic Approaches Technical Committee.
I started my academic journey with receiving my Bachelor of Technology in Mechanical Engineering from Malaviya National Institute of Technology, Jaipur, India in 2008. I moved to the U.S. in 2008 and earned my Master of Science in Mechanical Engineering from University of Florida in 2010. After, I continued as a Doctoral student under Prof. Raphael T. Haftka at University of Florida and received my PhD in Mechanical Engineering in December, 2014.
My research interests include multifidelity methods, machine learning in engineering, Monte Carlo methods, optimization under uncertainty, risk analysis, uncertainty quantification, surrogate-based design optimization, and use-inspired research.
Recent News
Jan 2024: I gave an invited lecture on Building trust in digital twins via explainable physics-based modeling and uncertainty quantification at the AIAA SciTech 2024 conference.
Dec 2023: Our work on predictive digital twins for brain cancer treatment was recently featured in the UT Austin News.
Nov 2023: I gave an invited lecture on our work Patient-specific digital twins for risk-aware treatment of high-grade gliomas at the 28th International Symposium of Yonsei Song-Dang Institute for Cancer Research.
Jul 2023: I presented our work on Patient-specific digital twins for risk-aware treatment of high-grade gliomas at the USNCCM conference in Albuquerque, NM.
More news
May 2023: I presented our work on Patient-specific predictive digital twin for optimizing radiotherapy regimens under uncertainty in high-grade gliomas at the Practical Big Data Workshop in Ann Arbor, MI.
January 2023: Ben Zastrow presented our collaborative work with Lockheed Martin on reduced-order modeling for coupled multi-physics problems at the AIAA SciTech 2023 conference.
January 2023: Vignesh Sella presented our work on multifidelity regression methods for data-poor applications at the AIAA SciTech 2023 conference.
January 2023: Our collaborative work with UC San Diego on multifidelity robust topology optimization was presented at the AIAA SciTech 2023 conference.
December 2022: Our work Certifiable Risk-Based Engineering Design Optimization is featured in the Aerospace America: 2022 Year in Review.
September 2021: I presented our work with ORNL collaborators on Goal-oriented active learning with Gaussian process surrogates for stability boundary identification and inverse model calibration in machining at the MMLDT conference.
December 2020: Our work IRIS-RBDO: Information reuse for importance sampling in reliability-based design optimization is featured in the Progress toward the 2030 vision for CFD in Aerospace America: 2020 Year in Review.
02/13/2020: Presented at Facebook Adaptive Experimentation Workshop in NY on Multifidelity Adaptive Experimental Design and Optimization Under Uncertainty.
January 2020: Our papers on Multifidelity Efficient Global Reliability Analysis and Information reuse for importance sampling in reliability-based design optimization are featured as novel advancements in probabilistic analysis in Aerospace America: 2019 Year in Review.
01/10/2020: Presented our work on Risk-Based Design Optimization Via Probability of Failure, Conditional Value-at-Risk, and Buffered Probability of Failure at AIAA SciTech conference in Orlando, Florida.
07/31/2019: Presented on Information Reuse for Importance Sampling in RBDO at the USNCCM in Austin, Texas.
04/19/2019: Gave the MIT ACDL Special Seminar on How to Reuse Information from Optimization History for Efficient Reliability-Based Design Optimization.
04/04/2019: Presented on Information Reuse for Importance Sampling in RBDO at the East Coast Optimization Meeting in Fairfax, Virginia.
04/03/2019: Gave a special seminar at NASA Goddard Space Flights Center on Multifidelity methods for Optimization Under Uncertainty: Fusing Models and Reusing Information.