Algorithmic Fairness and Social Choice
Core Stability for Public Projects
Approximate core for committee selection via multilinear extension and market clearing (with Y. Shen, K. Wang, and Z.Wang) SODA '22
Group Fairness in Data Science Applications
Fair for all: Best effort fairness in classification (with A. K. Krishnaswamy, Z. Jiang, K. Wang, and Y. Cheng) AISTATS '21
Mechanisms for Social Choice
Optimal algorithms for multiwinner elections and the Chamberlin-Courant Rule (with Zeyu Shen and Kangning Wang) EC '21.
Concentration of distortion: The value of extra voters in randomized social choice (with B. Fain and W. Fan) IJCAI '20.
Iterative local voting for collective decision-making in continuous spaces (with N. Garg, V. Kamble, A. Goel, and D. Marn) JAIR '19 (also in WWW '17).
Random dictatorship with random referee: Constant sample complexity mechanisms for social choice (with B. Fain, A. Goel, and N. Prabhu) AAAI '19.
Incentives and Planning in Resource Allocation
Auctions and Pricing
Optimal price discrimination for randomized mechanisms. (with Shao-Heng Ko) EC '22.
The limits of an information intermediary in auction design (with R. Alijani, S. Banerjee, and K. Wang) EC '22.
Predict and match: Prophet inequalities with uncertain supply. (with R. Alijani, S. Banerjee, S. Gollapudi, and K. Wang) SIGMETRICS '20.
The segmentation-thickness tradeoff in online marketplaces (with R. Alijani, S. Banerjee, K. Kollias, and S. Gollapudi) SIGMETRICS '19.
Scheduling and Routing
Dynamic weighted fairness with minimal disruptions (with Sungjin Im, Ben Moseley, and Kirk Pruhs). SIGMETRICS '20.
Competitive algorithms from competitive equilibria (with Sungjin Im and Janardhan Kulkarni) J. ACM '18. (Also in STOC '14 and FOCS '15)
ROBUS: Fair cache allocation for data parallel workloads (with Mayuresh Kunjir, Brandon Fain, and Shivnath Babu) SIGMOD '17.
Massively parallel algorithms for computing TIN DEMs and contour trees for large terrains (with P. K. Agarwal, K. Fox, and A. Nath) ACM GIS '16.
Stochastic regret minimization via Thompson sampling (with Sudipto Guha) COLT '14. See this related blog post on our conjecture.
On the precision of social and information networks (with Reza Bosagh Zadeh, Ashish Goel, and Aneesh Sharma), COSN '13.
Approximation algorithms for Bayesian multi-armed bandit problems (with Sudipto Guha) combines papers in STOC '07, ICALP '09, and APPROX '13.
Adaptive uncertainty resolution in Bayesian combinatorial optimization (with Sudipto Guha) TALG '12 (also in SODA '07).
Optimal auctions with positive network externalities (with Nima Haghpanah, Nicole Immorlica, and Vahab Mirrokni) EC '11.
Approximation algorithms for restless bandit problems (with Sudipto Guha and Peng Shi) J. ACM '10 (also in FOCS '07 and SODA '09).
Budget constrained auctions with heterogeneous items (with Sayan Bhattacharya, Gagan Goel, and Sreenivas Gollapudi) STOC '10.
Exceeding expectations and clustering uncertain data. (with Sudipto Guha), PODS '09.
Energy efficient monitoring of extreme values in sensor networks (with Adam Silberstein and Jun Yang) SIGMOD '06.
Asking the right questions: Model driven optimization using probes (with Ashish Goel and Sudipto Guha), PODS '06.
Cancer characterization and feature set extraction via discriminative margin clustering (with R. Tibshirani and P. O. Brown) BMC Bioinformatics 5:21, 2004.
Local search heuristics for k-medians and facility location problems (with V. Arya, N. Garg, R. Khandekar, A. Meyerson, and V. Pandit) STOC '01.
Slides and Videos
Talk on Multidimensional scheduling at the Optimization and Decision Making under Uncertainty Workshop, Simons Institute, 2016.