Elliot Anshelevich

For students who want to work with me:

I am usually looking for good PhD students to work with. I usually don't accept Masters students except in extraordinary circumstances.

Students applying to RPI:
If you are a student who is interested in algorithms, game theory, the study of networks, social choice, or any of the other topics mentioned on my webpage, I highly encourage you to apply to RPI. Please mark "Algorithms and Theory" as your primary or secondary interest, and mention that you would like to work with me in your application. This will ensure that I see your application and it will be given full consideration. Please also feel free to email me if you have any questions. Note that I get a lot of email, and I am much more likely to respond to email which mentions at least something related to my general research interests.

I do not offer summer internships to students who are not already at RPI, so please do not email me about those.

Students already at RPI:
Email me and come talk to me. However, unless you already have an extensive background in algorithms (more than just an introductory course), mathematics, game theory, or optimization, I highly suggest that you begin by taking my course "CSCI 4020 - Design and Analysis of Algorithms". After you see that you like these kinds of topics, and are good at them, please come talk to me. A good time would be about half-way through the semester.

My research interests:
My research interests are very broad, please see my webpage and (somewhat outdated) Research Statement. A lot of my research concerns algorithms, especially approximation algorithms. A lot of my work also concerns independent agents and game theory. This type of work considers a system in which there are a large number of agents which we cannot control, and which instead act in their own self-interest. This occurs, for example, in the Internet, in social networks, in transportation networks, in voting mechanisms, in auctions, and in a multitude of other interesting settings. More generally, I am interested in algorithmic and approximation problems in all sorts of settings, including network routing, graph algorithms, information propagation in networks, matching markets, etc.

If you are a student who might like to work with me and wants to learn more about my research, here are some of my papers that can give you the flavor of various problems I have worked on (see here for a full list, but the ones below serve as good starting points):

Yue Han, Chris Jerrett, and Elliot Anshelevich. Optimizing Multiple Simultaneous Objectives for Voting and Facility Location. Proc. of 37th Conference on Artificial Intelligence (AAAI 2023).
Elliot Anshelevich and Wennan Zhu. Ordinal Approximation for Social Choice, Matching, and Facility Location Problems given Candidate Positions. ACM Transactions on Economics and Computation (TEAC), Volume 9(2), Article 9. Conference version appeared in WINE 2018.
Elliot Anshelevich and Shreyas Sekar. Blind, Greedy, and Random: Algorithms for Matching and Clustering using only Ordinal Information. (slides) Proc. of 30th Conference on Artificial Intelligence (AAAI 2016).
Elliot Anshelevich, Onkar Bhardwaj, and John Postl. Approximating Optimal Social Choice under Metric Preferences. (slides) Proc. of 29th Conference on Artificial Intelligence (AAAI 2015).
Elliot Anshelevich and Martin Hoefer. Contribution Games in Social Networks. (slides) Algorithmica, Volume 63, Issue 1-2 (June 2012), pages 51-90. Conference version appeared in ESA 2010.
Elliot Anshelevich, Deeparnab Chakrabarty, Ameya Hate, and Chaitanya Swamy. Approximability of the Firefighter Problem: Computing Cuts over Time. (slides) Algorithmica, Volume 62, Issue 1 (2012), Pages 520-536.
Elliot Anshelevich and Sanmay Das. Matching, Cardinal Utility, and Social Welfare. ACM SIGecom Exchanges, Volume 9.1, June 2010.
Elliot Anshelevich, Anirban Dasgupta, Jon Kleinberg, Eva Tardos, Tom Wexler, and Tim Roughgarden. The Price of Stability for Network Design with Fair Cost Allocation. SIAM Journal on Computing, Volume 38, Issue 4 (November 2008), pp. 1602-1623. Conference version appeared in FOCS 2004.

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