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Anirban Dasgupta studies algorithms for large datasets, networks and related learning problems. His IIT Gandhinagar profile identifies large-scale data algorithms and social networks among his research interests.^[ref]

He coauthored The Price of Stability for Network Design with Fair Cost Allocation by Elliot Anshelevich and others and Near-Optimal Network Design with Selfish Agents by Elliot Anshelevich and others. These works connect network optimization with individual route choices. A centrally cheap collection of paths may fail to persist if users can reduce their own payments by switching; conversely, a stable collection need not minimize the total cost.^[ref]

The algorithmic challenge is to control both quantities at once: computational work required to find a network and inefficiency introduced by decentralized decisions. That is a concrete bridge between approximation guarantees and strategic behavior.

By Elliot Anshelevich, Anirban Dasgupta, Éva Tardos, Tom Wexler.

Theory of Computing 4 (2008), 77–109; published 4 August 2008; DOI 10.4086/toc.2008.v004a004. Abstract: strategic connection game and approximate equilibria. Primary author biographies and identified portraits: toc.cs.uchicago.edu/articles/v004a004/about.html .

By Elliot Anshelevich, Anirban Dasgupta, Jon Kleinberg, Éva Tardos, Tom Wexler, Tim Roughgarden.

Author-hosted manuscript dated 17 June 2004. Introduction defines the cost ratio for the best Nash equilibrium and explains the stable-recommendation interpretation.