My research focuses on designing provable algorithms for optimization problems. I draw ideas from multiple areas of mathematics including graph theory, fixed and high dimensional geometry, algebraic topology, and decision theory. More recently, I have also ventured into machine learning and have on-going efforts to improve the state-of-the-art for the traveling salesman problem as well as the k-server problems. Specific research directions include but are not limited to the following areas:

  • Matching
  • Online Algorithms
  • Optimal Transport
  • Topological Data Analysis
  • Geometric Optimization

Funding & Awards

“Efficient Algorithms for Optimal Transport in Geometric Settings” (NSF), $308,000, Jun’22- Jun’25.

“Algorithms for Fundamental Optimization Problems in Computational Geometry” (NSF), $450,000, Jul’19- Jun’23

“The Geometry Behind Logistics ‐ Approximation Algorithms for Real‐Time Delivery” (NSF CRII), $175,000, Feb’15- Jan’18