About Me
I am currently a Senior Machine Learning Research Scientist at Lawrence Livermore National Laboratory. I received my Ph.D. degree at the University of California, Berkeley, where I was a member of the Mechanical Systems Control Lab and I was advised by Prof. Masayoshi Tomizuka.
Working on multiple AI for science projects (e.g. physics, healthcare, biology) where machine learning techniques are leveraged to advance scientific research and discovery. I have served as PI and Co-PI in several Cooperative Research and Development Agreements (CRADAs) funded by the Department of Energy’s Advanced Manufacturing Office (AMO). These collaborations involve working with energy-intensive industries with the aim of minimizing energy consumption.
Our team is actively seeking research collaborations. Please feel free to reach out if you are interested.
Education
- Ph.D. — University of California, Berkeley, 2021
- Major: Control
- Minor: Machine Learning, Optimization
- B.S. — University of Illinois at Urbana-Champaign, 2016
- Major: Mechanical Engineering
- Minor: Electrical and Computer Engineering
Recent News
- 09/2025: One paper on mesh graph based surrogate modeling for dynamic systems is accepted by TMLR!
- 07/2025: One paper on interpreting CFD surrogates is accepted by the XAI workshop on IJCAI 2025!
- 01/2025: One paper on innovative visual localization system for robotic agents is accepted by T-RO!
- 12/2024: Two papers on post-combustion carbon capture surrogate modeling are accepted by Frontier in AI! [paper1] [paper2]
- 06/2024: Recieve the LLNL Global Security Silver Award for excellent management and execution of the HPC4EI project!
- 05/2024: Our HPC4EI project with ArcelorMittal received 2nd place in AI category for the best Emerging Technology Awards, 2024!
- 05/2024: Promoted to Senior Staff Scientist!
- 01/2024: One paper towards creating generalizable and interpretable prediction model is accecpted by AISTATS 2024!
- 07/2023: Check out our promotion video for our accepted 2023 KDD paper!
- 06/2023: One paper on driving behavior generation is accepted by RA-L!
- 05/2023: One paper on ML for dynamic system modeling is accepted by KDD 2023!
- 03/2023: Two papers on physically-based simulation are accepted by ICLR 2023 Physics for Machine Learning Workshop!
- 02/2023: Selected as Rising Stars in Computational & Data Sciences!