Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service
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Data-Driven Prediction of Route-Level Energy Use for Mixed-Vehicle Transit Fleets
Published in 2020 IEEE International Conference on Smart Computing (SMARTCOMP), 2020
Recommended citation: Ayman, A., Wilbur, M., Sivagnanam, A., Pugliese, P., Dubey, A., & Laszka, A. (2020, September). Data-driven prediction of route-level energy use for mixed-vehicle transit fleets. In 2020 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 41-48). IEEE.
Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service
Published in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-21), 2021
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).
Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles
Published in ACM Transactions on Internet Technology, 2021
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.
Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit
Published in Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22), 2022
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)
The Benefits of Vulnerability Discovery and Bug Bounty Programs: Case Studies of Chromium and Firefox
Published in Proceedings of the ACM Web Conference (WWW-23), 2023
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
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Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service
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).
On the Benefits of Bug Bounty Programs: A Study of Chromium Vulnerabilities
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).
workshops
On the Benefits of Bug Bounty Programs: A Study of Chromium Vulnerabilities
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).