Hi, I am a final-year PhD student advised by Justin Solomon in Geometric Data Processing group. My research interest is in applying geometric tools to tackle problems in optimization, statistics, and computer graphics. I am grateful to have interned at Microsoft Research New England with Lester Mackey and Adobe Research with Noam Aigerman and Vova Kim during my PhD.
Before coming to MIT, I obtained my Bachelor's Degree in Computer Science and Mathematics and my Master's Degree in Mathematics, both at Stanford University. During my time at Stanford, I was fortunate to have worked with Leonidas Guibas and Daniel Bump, among many others.
Research
Debiased Distribution Compression
International Conference on Machine Learning (ICML 2024), Vienna
![](assets/img/paper_thumbnails/ddc.png)
Self-Consistent Velocity Matching of Probability Flows
Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA
![](assets/img/paper_thumbnails/scvm.png)
Sampling with Mollified Interaction Energy Descent
Conference on Learning Representations (ICLR 2023), Kigali
![](assets/img/paper_thumbnails/mied.png)
Learning Proximal Operators to Discover Multiple Optima
Conference on Learning Representations (ICLR 2023), Kigali
![](assets/img/paper_thumbnails/prox_multi.png)
Wasserstein Iterative Networks for Barycenter Estimation
Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA
![](assets/img/paper_thumbnails/c2wb_itr.png)
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark
Conference on Neural Information Processing Systems (NeurIPS 2021), online
![](assets/img/paper_thumbnails/w2benchmark.jpg)
Large-Scale Wasserstein Gradient Flows
Conference on Neural Information Processing Systems (NeurIPS 2021), online
![](assets/img/paper_thumbnails/gf_icnn.jpg)
Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
Conference on Learning Representations (ICLR 2021), online
![](assets/img/paper_thumbnails/c2wb.png)
Continuous Regularized Wasserstein Barycenters
Conference on Neural Information Processing Systems (NeurIPS 2020), online
![](assets/img/paper_thumbnails/cwb.png)
Supervised Fitting of Geometric Primitives to 3D Point Clouds
Oral Presentation
Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA
![](assets/img/paper_thumbnails/spfn.png)
Branching Rules of Classical Lie Groups in Two Ways
Undergraduate honors thesis. Stanford University, 2018
![](assets/img/paper_thumbnails/branching.png)