Artificial Intelligence, Machine Learning, Deep Reinforcement Learning, Optimization, Operational Research
Sivagnanam, A., Pettet, A., Lee, H., Mukhopadhyay, A., Dubey, A., & Laszka, A. (2024). Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing. In Proceedings of the 41 st International Conference on Machine Learning, (ICML 2024)
Atefi, S., Sivagnanam, A., Ayman, A., Grossklags, J., & Laszka, A. (2023, May). The Benefits of Vulnerability Discovery and Bug Bounty Programs: Case Studies of Chromium and Firefox. In Proceedings of the ACM Web Conference, (pp 2209–2219), ACM
Sivagnanam, A., Kadir, SU., Mukhopadhyay, A., Pugliese, P., Dubey, A., Samaranayake, S., & Laszka, A. (2022, July) "Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (pp. 3933-3939)
Ayman, A., Sivagnanam, A., Wilbur, M., Pugliese, P., Dubey, A., & Laszka, A. (2021). Data-driven prediction and optimization of energy use for transit fleets of electric and ICE vehicles. ACM Transactions on Internet Technology (TOIT), 22(1), 1-29.
Sivagnanam, A., Ayman, A., Wilbur, M., Pugliese, P., Dubey, A., & Laszka, A. (2021, May). Minimizing energy use of mixed-fleet public transit for fixed-route service. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 17, pp. 14930-14938).
Talk at Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22), Vienna, Austria
Talk at The 20th Annual Workshop on the Economics of Information Security (WEIS 2021), Virtual Workshop
Talk at Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-21), Virtual Conference
Sivagnanam, A., Atefi, S., Ayman, A., Grossklags, J., & Laszka, A. (2021). On the Benefits of Bug Bounty Programs: A Study of Chromium Vulnerabilities. In Workshop on the Economics of Information Security (WEIS) (Vol. 10).