Kamesh Munagala

Kamesh Munagala is a Professor of Computer Science at Duke University's Department of Computer Science. His research focuses on theoretical computer science, particularly approximation algorithms, online algorithms, and computational economics. His work addresses challenges in resource allocation, decision making, and provisioning, with applications in data networks, facility location, data center scheduling, ad slot allocation, ride-share scheduling, and civic budgeting. Recent research interests include persuasion through information revelation and pricing, fairness in resource allocation, and multi-agent systems. He has published in top conferences such as STOC, SODA, and WINE, and teaches courses on algorithmic game theory, algorithm design, and randomized algorithms.

Kamesh Munagala is a Professor of Computer Science at Duke University, specializing in Algorithms, Algorithmic Game Theory, Decision Sciences, and Big Data. His research focuses on developing efficient algorithms for complex optimization problems, including facility location, clustering, and network design. He explores the intersection of algorithmic techniques with real-world applications such as sensor networks, social networks, and web services. His work addresses challenges in query optimization, resource allocation, and fair allocation of public goods. Munagala's contributions span approximation algorithms, online algorithms, and the design of distributed systems for large-scale data processing.