Kamesh Munagala, Professor of Computer Science

Please note: Kamesh has left Center for Theoretical & Mathematical Sciences at Duke University; some info here might not be up to date.

Contact Info:

Office Location:	D205, Lsrc, Research Drive, Durham, NC 27708
Email Address:
Web Page:	https://www.kameshmunagala.org

Teaching (Spring 2024):  (typical courses)

• COMPSCI 535.01, ALGORITHMIC GAME THEORY Synopsis

  Old Chem 116, WF 01:25 PM-02:40 PM

• COMPSCI 330.001, DESIGN/ANALY ALGORITHMS Synopsis

  FFSC 2231, WF 01:25 PM-02:40 PM

• COMPSCI 330.01D, DESIGN/ANALY ALGORITHMS Synopsis

  LSRC D243, M 08:30 AM-09:45 AM

• COMPSCI 330.02D, DESIGN/ANALY ALGORITHMS Synopsis

  Physics 227, M 10:05 AM-11:20 AM

• COMPSCI 330.03D, DESIGN/ANALY ALGORITHMS Synopsis

  TBA, M 10:05 AM-11:20 AM

• COMPSCI 330.04D, DESIGN/ANALY ALGORITHMS Synopsis

  LSRC A155, M 10:05 AM-11:20 AM

• COMPSCI 330.05D, DESIGN/ANALY ALGORITHMS Synopsis

  TBA, M 11:45 AM-01:00 PM

• COMPSCI 330.06D, DESIGN/ANALY ALGORITHMS Synopsis

  Gross Hall 103, M 01:25 PM-02:40 PM

• COMPSCI 330.07D, DESIGN/ANALY ALGORITHMS Synopsis

  TBA, M 03:05 PM-04:20 PM

Education:

Ph.D.	Stanford University	2003
M.S.	Stanford University	2002
B.Tech	Indian Institute of Technology Bombay	1998

Specialties:

Algorithms

Research Interests:

My main research interest is algorithm design for emerging database and networking systems. My current focus is on approximate policy design for stochastic decision problems and its applications to database query optimization and wireless networks. I have also worked on approximation and online algorithms for network design and clustering applications, on DNA microarray analysis, and on I/O-efficient algorithms.

Areas of Interest:

Approximation Algorithms
Stochastic Decision Theory
Algorithmic Game Theory
Query Optimization and Database Theory
Data Mining

Keywords:

Modeling • Recall • Social networks

Recent Publications   (More Publications)   (search)

1. Banerjee, S; Munagala, K; Shen, Y; Wang, K, Fair Price Discrimination, Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms, vol. 2024-January (January, 2024), pp. 2679-2703 [doi]  [abs]
2. Munagala, K; Sankar, GS; Taylor, E, Probabilistic Metric Embedding via Metric Labeling, Leibniz International Proceedings in Informatics, LIPIcs, vol. 275 (September, 2023), ISBN 9783959772969 [doi]  [abs]
3. Mavrov, IA; Munagala, K; Shen, Y, Fair Multiwinner Elections with Allocation Constraints, EC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation (July, 2023), pp. 964-990, ISBN 9798400701047 [doi]  [abs]
4. Bhaskara, A; Gollapudi, S; Im, S; Kollias, K; Munagala, K, Online Learning and Bandits with Queried Hints, Leibniz International Proceedings in Informatics, LIPIcs, vol. 251 (January, 2023), ISBN 9783959772631 [doi]  [abs]
5. Bhaskara, A; Munagala, K, Competing against Adaptive Strategies in Online Learning via Hints, Proceedings of Machine Learning Research, vol. 206 (January, 2023), pp. 10409-10424  [abs]