I am a PhD student in the CSE department at UCSD. I started in Fall 2020 and did my undergraduate degree in computer science and math at Carleton College. My advisor is Yusu Wang and currently, I work on research relating to optimal transport, neural networks, geometric deep learning, and geometric algorithms/problems.

Publications

De-Coupled NeuroGF for Shortest Path Distance Approximations on Large Terrains (S. Chen, P. K. Agarwal, Y. Wang, accepted to ICML 2025)

Graph neural networks extrapolate out-of-distribution for shortest paths (R. R. Nerem, S. Chen, S. Dasgupta, Y. Wang, preprint 2025)

Neural approximations of Wasserstein distance via a universal architecture for symmetric and factor-wise group invariant functions (S. Chen, Y. Wang, accepted to NeurIPS 2023)

Learning Ultrametric Trees for Optimal Transport Regression (S. Chen, P. Tabaghi, Y. Wang, accepted to AAAI 2024)

The Weisfeiler-Lehman Distance: Reinterpretation and Connetion GNNs (S. Chen, S. Lim, F. Mémoli, Z. Wan, Y. Wang, ICML workshop: Topology, Algebra, and Geometry in Machine Learning (2023))

Weisfeiler-Lehman meets Gromov-Wasserstein (S. Chen, S. Lim, F. Mémoli, Z. Wan, Y. Wang, accepted to ICML 2022)

Approximation algorithms for 1-Wasserstein distance between persistence diagrams (S. Chen, Y. Wang, accepted to SEA 2021)

Links to cool people(labmates, collaborators, friends, and enemies)

Sowmya Manojna Narasimha, Dhruv Kohli, Zhengchao Wan, Tristan Brugere, Jesse He, Riley Nerem