computational social choice

when you care about fairness, representation, collective decision making, and incentives

This focus area studies algorithmic and computational aspects of combining individual preferences and interests into collective decisions. It encompassed coalition formation, preference aggregation, ranking systems, resource allocation, and voting.

selected papers

  1. Shengxin Liu, Xinhang LuMashbat Suzuki, and Toby Walsh
    Mixed Fair Division: A Survey
    Journal of Artificial Intelligence Research, 2024
  2. EC
    Maximum Flow is Fair: A Network Flow Approach to Committee Voting
    In Proceedings of the 25th ACM Conference on Economics and Computation, EC 2024, New Haven, CT, USA, July 8-11, 2024, 2024
  3. ITCS
    Siddharth Barman, Anand Krishna, Pooja Kulkarni, and Shivika Narang
    Sublinear Approximation Algorithm for Nash Social Welfare with XOS Valuations
    In 15th Innovations in Theoretical Computer Science Conference, ITCS 2024, January 30 to February 2, 2024, Berkeley, CA, USA, 2024
  4. NeurIPS
    Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism
    In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022
  5. Kai Li, Chau Yuen, Branislav Kusy, Raja Jurdak, Aleksandar Ignjatovic, Salil S. Kanhere, and Sanjay Jha
    Fair Scheduling for Data Collection in Mobile Sensor Networks with Energy Harvesting
    IEEE Transactions on Mobile Computing, 2019
  6. FOCS
    A Discrete and Bounded Envy-Free Cake Cutting Protocol for Any Number of Agents
    In IEEE 57th Annual Symposium on Foundations of Computer Science, FOCS 2016, 9-11 October 2016, Hyatt Regency, New Brunswick, New Jersey, USA, 2016