I’m an incoming master’s student at Northeastern University and an NSF Graduate Research Fellow (GRFP) in artificial intelligence. I am advised by Professor Robin Walters in the Geometric Learning Lab, as well as a research assistant at MIT Lincoln Laboratory.
My research interest is robust and interpretable machine learning for physical systems. Recently, this has been through creating physics-informed deep dynamics models, and using these models for generative mesh design. I have also previously applied my work to robot learning.
Updates
- (04/24) I was selected as a National Science Foundation Graduate Research Fellow (GRFP). I will be continuing my research during a master’s program at Northeastern University.
- (03/24) Check out this news article about my work.
- (12/23) Attending NeurIPS 2023 in-person.
- (11/23) I’ll be at Boston Symmetry Day at MIT, presenting our work on equivariant drag coefficient modeling.
- (10/23) Our work on equivariant drag coefficient modeling was accepted to the NeurIPS 2023 Workshop on Symmetry and Geometry in Neural Representations (NeurReps).
- (09/23) This Fall, I am pursuing full-time machine learning research at MIT Lincoln Laboratory as a co-op student.
- (05/23) I began my internship at Blue Origin working on avionics software for the New Shepard rocket.
- (04/23) I’m presenting our work on equivariant learning with latent symmetries at RISE, Northeastern’s annual research expo. See my poster here.
- (02/23) I was awarded a PEAK Award by the Northeastern Undergraduate Research and Fellowships office for my exploratory work on efficient equivariant control for satellite formation flying.
- (01/23) Our work on equivariant learning with latent symmetries was accepted spotlight (notable-top-25%) to ICLR 2023.
Education
- (2020 - 2024)
Northeastern University
B.S. Computer Science, Minor in Mathematics