77 Massachusetts Ave, Bldg 6C-411

Cambridge, MA 02139

I am a physics Ph.D. student in Marin Soljačić’s group at MIT. I work at the intersection of physics and machine learning, and my research interests include physics-informed machine learning, condensed matter physics, nonlinear dynamics, and photonics. I am more broadly interested in developing new computational methods for simulating and understanding physical systems with an emphasis on incorporating physics-based priors and providing interpretability.

I received my A.B. in Physics and Mathematics from Harvard College in 2016 and am currently pursuing a Ph.D. in Physics at MIT.

## Selected Publications

1. Discovering Sparse Interpretable Dynamics from Partial Observations
2021
2. Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems
2021
3. Extracting Interpretable Physical Parameters from Spatiotemporal Systems Using Unsupervised Learning
Phys. Rev. X 2020
4. Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery
IEEE Transactions on Neural Networks and Learning Systems 2021