Published:
Recommended citation: 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)
Published:
Recommended citation: 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)
Published:
Recommended citation: 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
Published:
Recommended citation: 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)
Published:
[Paper] [Appendix] [Code and Data]
Recommended citation: 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)
Published:
Recommended citation: 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
Published:
[Paper] [Appendix] [Code and Data] [Official Video]
Recommended citation: 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)
Published:
Recommended citation: 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
Published:
[OpenReview] [PMLR] [Code and Data] [ShortVideo]
Recommended citation: 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)
Published:
[Slides] [Poster] [Paper] [Appendix] [Code and Data]
Recommended citation: 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)
Published:
Recommended citation: 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)
Published:
Recommended citation: 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)