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Kamesh Munagala

Professor of Computer Science
Computer Science
Box 90129, Computer Science Department, Durham, NC 27708-0129
D205, LSRC, Research Drive, Durham, NC 27708

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.

Current Appointments & Affiliations


Professor of Computer Science · 2016 - Present Computer Science, Trinity College of Arts & Sciences

Recent Publications


Optimal algorithms for multiwinner elections and the Chamberlin–Courant Rule

Conference Social Choice and Welfare · February 1, 2025 We consider the algorithmic question of choosing a subset of candidates of a given size k from a set of m candidates, with knowledge of voters’ ordinal rankings over all candidates. We consider the well-known and classic scoring rule for achieving diverse ... Full text Cite

Majorized Bayesian Persuasion and Fair Selection

Conference Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms · January 1, 2025 We address the fundamental problem of selection under uncertainty by modeling it from the perspective of Bayesian persuasion. In our model, a decision maker with imperfect information always selects the option with the highest expected value. We seek to ac ... Cite

Optimal Price Discrimination for Randomized Mechanisms

Journal Article ACM Transactions on Economics and Computation · June 12, 2024 We study the power of price discrimination via an intermediary in bilateral trade, when there is a revenue-maximizing seller selling an item to a buyer with a private value drawn from a prior. Between the seller and the buyer, there is an intermediary that ... Full text Cite
View All Publications

Recent Grants


III: Medium: Responsive Optimization for Algorithmic Decision Systems

ResearchCo-Principal Investigator · Awarded by National Science Foundation · 2024 - 2027

AF: Small: Algorithm and Incentive Design for Modern Resource Allocation Platforms

ResearchPrincipal Investigator · Awarded by National Science Foundation · 2021 - 2025

HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms

ResearchSenior Investigator · Awarded by National Science Foundation · 2019 - 2023

View All Grants

Education, Training & Certifications


Stanford University · 2003 Ph.D.
Stanford University · 2002 M.S.

External Links


Personal Webpage