Guanghao Ye (叶光昊)

I am a first-year PhD student at MIT. Prior to that, I spent four wonderful years at University of Washington, where I was very fortunate to be advised by Prof. Yin Tat Lee.  I am broadly interested in theoretical computer science.

Papers/Manuscripts

• A Gradient Sampling Method with Complexity Guarantees for Lipschitz Functions in High and Low Dimensions
  with Damek Davis, Dmitriy Drusvyatskiy, Yin Tat Lee, and Swati Padmanabhan
  In submission
• Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly Linear Time
  with Sally Dong, Yu Gao, Gramoz Goranci, Yin Tat Lee, Richard Peng, and Sushant Sachdeva
  SODA 2022
• A Nearly-Linear Time Algorithm for Linear Programs with Small Treewidth: A Multiscale Representation of Robust Central Path
  With Sally Dong and Yin Tat Lee
  STOC 2021
  Invited to SICOMP Special Issue.
• Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time
  with Jerry Li
  NeurIPS 2020
• Fast Algorithm for Solving Structured Convex Programs 
  Undergraduate Thesis
  Best Senior Thesis Award Honorable Mention.

Contact

Email: ghye at mit edu
Office: 2-490