Research Overview

My research is in the general area of theoretical computer science, particularly the areas of Approximation Algorithms, Online Algorithms, and Computational Economics.  I work on developing models, algorithms, and markets for resource allocation, decision making, and provisioning problems. These problems arise in a variety of applications -- designing a data network, facility location and clustering, data center scheduling, allocating ad slots, scheduling ride-shares, and civic budgeting.  In these contexts, my work has addressed several research challenges. 

• Intractability: Exactly optimal solutions are often inefficient to  compute due to the discrete, combinatorial nature of the problems, and we seek efficient algorithms that compute provably approximate optimal solutions. 

• Uncertainty: When future demand is uncertain, we seek algorithms that either work with specified models of uncertainty, or are robust to any possible future.

• Pricing and Incentives: In settings where participants may lie about the utility of resources to them, we seek to design appropriate pricing schemes and incentives.

• Fairness: In settings where resources are shared and the allocation has to be fair to the participants, we seek models for fairness and devise efficient algorithms for these models.

I am part of the  Algorithms group  and the Computational Economics group.

Some Recent Publications

A complete list of my papers is available on DBLP and on Google Scholar.  See here for more papers and projects.

• • Fair price discrimination. 

  • Fair multiwinner elections with allocation constraints. EC '23

  • Online learning and bandits with queried hints. ITCS '23

  • All politics is local: Redistricting via local fairness. NeurIPS '22

  • Auditing for core stability in Participatory Budgeting. WINE '22

  • Optimal price discrimination for randomized mechanisms. EC '22

  • The limits of an information intermediary in auction design. EC '22

  • Approximate core for committee selection via multilinear extension and market clearing. SODA '22

Recent Courses

Please see here for a complete list of courses.

• Spring '23, '21: CPS 230: Discrete Mathematics

• Fall '21:   CPS 330:  Algorithm Design

• Fall '20: CPS 532: Graduate Algorithms

• Spring '20:  CPS 630: Randomized Algorithms

• Spring '19:  CPS590:  Algorithms for Decision making at Scale

Contact Information

D205, Levine Science Research Center, 

308 Research Drive, Durham NC 27708-0129.

Phone: (919) 660-6598

Email address: <first_name> @cs.duke.edu