• Associate Professor, Computer Science & Engineering
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Image of Guni Sharon

Educational Background

  • Ph.D. in Information Systems Engineering, Ben-Gurion University — 2015
  • M.S. in Information Systems Engineering, Ben-Gurion University — 2012
  • B.S. in Information Systems Engineering, Ben-Gurion University — 2011

Research Interests

    • Reinforcement learning
    • Combinatorial search
    • Intelligent transportation systems
    • Multiagent pathfinding
    • Algorithmic game theory
    • Flow and convex optimization
    • Multiagent modeling and simulation

Awards & Honors

  • Keynote speaker, “Wilson Memorial Lecture,” The Research Council on Mathematics Learning – 2025
  • Bergmann Memorial Research Award, Binational Science Foundation – 2024
  • NSF ‘CAREER’ Award, National Science Foundation – 2023
  • Early-Career Spotlight invited talk (“Alleviating Road Traffic Congestion with Artificial Intelligence”), 30th International Joint Conference on Artificial Intelligence (IJCAI-21) – 2021
  • 2020 Prominent Paper Award (“Conflict-based Search for Optimal Multi-agent Pathfinding”), the journal of Artificial Intelligence (AIJ) – 2020
  • Faculty Teaching Excellence Award, Computer science and engineering, Texas A&M University – 2019
  • Outstanding Paper Award (“Bidirectional Search that is Guaranteed to Meet in the Middle”), AAAI Conference on Artificial Intelligence – 2016
  • Best Paper Award (“Meta-Agent Conflict-Based Search for Optimal Multi-Agent Path Finding”), International Symposium on Combinatorial Search (SOCS-12) – 2012

Selected Publications

  • G Sharon, R Stern, A Felner, NR Sturtevant. “Conflict-based search for optimal multi-agent pathfinding.” Artificial Intelligence 219, 40-66.
  • G Sharon, P Stone. “A protocol for mixed autonomous and human-operated vehicles at intersections.” Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems, 151-167.
  • J Ault, G Sharon. “Reinforcement learning benchmarks for traffic signal control.” Thirty-fifth Conference on Neural Information Processing Systems.
  • J Ault, J Hanna, G Sharon. “Learning an Interpretable Traffic Signal Control Policy.” Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 88-96.
  • G Sharon, MW Levin, JP Hanna, T Rambha, SD Boyles, P Stone. “Network-wide adaptive tolling for connected and automated vehicles.” Transportation Research Part C: Emerging Technologies 84, 142-157.
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