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

Lingxiao Li, Raaz Dwivedi, Lester Mackey

Preprint

Self-Consistent Velocity Matching of Probability Flows

Lingxiao Li, Samuel Hurault, Justin Solomon

Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA

Sampling with Mollified Interaction Energy Descent

Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon

Conference on Learning Representations (ICLR 2023), Kigali

Learning Proximal Operators to Discover Multiple Optima

Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon

Conference on Learning Representations (ICLR 2023), Kigali

Wasserstein Iterative Networks for Barycenter Estimation

Alexander Korotin, Vage Egiazarian, Lingxiao Li, Evgeny Burnaev

Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA

Interactive All-Hex Meshing via Cuboid Decomposition

Lingxiao Li, Paul Zhang, Dmitriy Smirnov, Mazdak Abulnaga, Justin Solomon

SIGGRAPH Asia 2021, Tokyo

Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark

Alexander Korotin, Lingxiao Li, Aude Genevay, Justin Solomon, Alexander Filippov, Evgeny Burnaev

Conference on Neural Information Processing Systems (NeurIPS 2021), online

Large-Scale Wasserstein Gradient Flows

Petr Mokrov*, Alexander Korotin*, Lingxiao Li, Aude Genevay, Justin Solomon, Evgeny Burnaev

Conference on Neural Information Processing Systems (NeurIPS 2021), online

Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization

Alexander Korotin, Lingxiao Li, Justin Solomon, Evgeny Burnaev

Conference on Learning Representations (ICLR 2021), online

Continuous Regularized Wasserstein Barycenters

Lingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin Solomon

Conference on Neural Information Processing Systems (NeurIPS 2020), online

Supervised Fitting of Geometric Primitives to 3D Point Clouds

Lingxiao Li*, Minhyuk Sung*, Anastasia Dubrovina, Li Yi, Leonidas Guibas

Oral Presentation
Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA

Branching Rules of Classical Lie Groups in Two Ways

Lingxiao Li

Undergraduate honors thesis. Stanford University, 2018