About Me

I am a fifth-year Ph.D. student at the University of Illinois, Urbana-Champaign, and part of the Theory Group. I am fortunate to be advised by Prof. Jugal Garg and Prof. Ruta Mehta. My research focuses on issues of fairness, efficiency, and incentives in problems at the intersection of algorithms, game theory, and machine learning.

During my PhD, I interned with the Infrastructure Optimization Research (IOR) team at Google Research, and the Real Time Algorithms Team at Adobe Research. Before my PhD, I completed my MS in Computer Science from UIUC and undergrad from IIT Bombay.

I am the recepient of the Mavis Future Faculty Fellowship, the Siebel Scholarship and the IIT Bombay Academic Prize.

Here is my CV, and my PhD Thesis Proposal document containing an overview of my PhD research.

Publications

1. Constant-Factor EFX Exists for Chores.
   

   Symposium on Theory of Computing (STOC 2025) (STOC 2025).
   Jugal Garg, Aniket Murhekar, John Qin

2. On the Theoretical Foundations of Data Exchange Economies.
   

   Under submission at EC 2025.
   Hannaneh Akrami, Bhaskar Ray Chaudhary, Jugal Garg, Aniket Murhekar

3. Fair Federated Learning via the Proportional Veto Core.
   

   International Conference on Machine Learning (ICML) (ICML 2024).
   Bhaskar Chaudhary*, Aniket Murhekar*, Zhuowen Yuan*, Bo Li, Ruta Mehta, Ariel Procaccia

4. Weighted EF1 and PO Allocations with Few Types of Agents or Chores.
   

   International Joint Conference on Artificial Intelligence (IJCAI) (IJCAI 2024).
   Jugal Garg, Aniket Murhekar, John Qin

5. Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization.
   

   Neural Information Processing Systems (NeurIPS) (NeurIPS 2023).
   Aniket Murhekar, Bhaskar Chaudhary, Zhuowen Yuan, Bo Li, Ruta Mehta

6. Dynamic Vector Bin Packing for Resource Allocation on the Cloud.
   

   Symposium on Parallelism in Algorithms and Architectures (SPAA 2023).
   Aniket Murhekar, David Arbour, Tung Mai, Anup Rao

7. New Algorithms for the Fair and Efficient Allocation of Indivisible Chores.
   

   International Joint Conference on Artificial Intelligence (IJCAI 2023).
   Jugal Garg, Aniket Murhekar, John Qin

8. Nash Equilibria in Two Player Games Repeated Until Collision.
   

   Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2023).
   Aniket Murhekar, Eklavya Sharma

9. (Almost) Envy-Free, Proportional and Efficient Allocations of an Indivisible Mixed Manna.
   

   International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2022).
   Vasilis Livanos, Ruta Mehta, Aniket Murhekar

10. Tractable Fragments of the Maximum Nash Welfare Problem.
    

    Conference on Web and Internet Economics (WINE 2022).
    Jugal Garg, Edin Husic, Aniket Murhekar, Laszlo Vegh

11. Fair and Efficient Allocations of Bivalued Chores.
    

    AAAI Conference on Artificial Intelligence (AAAI 2022).
    Jugal Garg, Aniket Murhekar, John Qin

12. On Fair and Efficient Allocations of Indivisible Public Goods.
    

    Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2021).
    Jugal Garg, Pooja Kulkarni, Aniket Murhekar.

13. Computing Fair and Efficient Allocations with Few Utility Values.
    

    International Symposium on Algorithmic Game Theory (SAGT 2021).
    Jugal Garg, Aniket Murhekar.

14. On Fair and Efficient Allocations of Indivisible Goods.
    

    AAAI Conference on Artificial Intelligence (AAAI 2021).
    Jugal Garg, Aniket Murhekar.

15. Approximate Nash Equilibria of Imitation Games: Algorithms and Complexity.
    

    International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020).
    Aniket Murhekar, Ruta Mehta.

16. Near-optimal complexity bounds for fragments of the Skolem Problem.
    

    Symposium on Theoretical Aspects of Computer Science. (STACS 2020).
    S. Akshay, N. Balaji, A. Murhekar, R. Varma, and N. Vyas.

17. Vocabulary Tailored Summary Generation.
    

    International Conference on Computational Linguistics. (COLING 2018).
    K. Krishna, A. Murhekar, S. Sharma, B. Srinivasan.

18. Automated Recurrence Analysis for Almost-Linear Expected-Runtime Bounds.
    

    Computer Aided Verification. (CAV 2017).
    K. Chatterjee, H. Fu, and A. Murhekar.