About me

I am an Assistant Professor in the Department of Mathematics and Statistics at Old Dominion University (ODU) and am affiliated with the School of Data Science. Before joining ODU, I was a postdoctoral researcher and guest scientist in the Applied Mathematics and Plasma Physics (T-5) Group at LANL from 2022 to 2024. Prior to that, I worked as a Senior ML Engineer and core team member at SGR Semiconductor Inc., an AI startup where I led a team developing AI-enabled mmWave sensors for detecting human movement in smart devices (2021-2022). I also held postdoctoral positions at the Courant Institute of Mathematical Sciences, NYU (2020-2021), and Oak Ridge National Laboratory (2017-2019). I received Ph.D. in Mathematics from Virginia Tech in 2017.

I am a computational scientist and applied mathematician by training. I have been honored and grateful to work with talented mathematicians, physicists, and computer scientists. My primary areas of interest are reduced order modeling and scientific machine learning for complex systems. Additionally, I am interested in exploring the mathematical foundations of AI and enhancing the interpretability of AI models.

Recent News

  • Aug. 2025, I am pleased to announce that my group received an award providing 4000 GPU hours and 15000 CPU node hours on Perlmutter through the NERSC AI4Science program!

  • May 2025, I gave a talk on ROM for Geophysical fluids with ML at the 2025 NSF computation mathematics meeting. I appreciate the travel support provided by the NSF.

  • Mar. 2025, I co-organized a minisymposium on ROMs and ML for fluids at the SIAM CSE25 conference.

  • Jan. 2025, I am happy to serve as a TPC member for the 62th ACM/IEEE Design Automation Conference (DAC2025) in the "A1. AI/ML Algorithms" track!

  • Nov. 2024, I gave a talk on Physics-integrated Latent Spaces Dynamics Learning for CR model at the AAAI 2024 Fall Symposium, Arlington, VA.

  • Nov. 2024, I gave a talk on Data-driven reduced order modeling at the MAA MD-DC-VA section meeting Fall