Education
Operations Research & Financial Engineering, PhD, Princeton University
External Links
Recent Publications
Cui, K., Dayanıklı, G., Laurière, M., Geist, M., Pietquin, O., & Koeppl, H. (2024). Learning Discrete-Time Major-Minor Mean Field Games. In M. Wooldridge, J. Dy, & S. Natarajan (Eds.), Technical Tracks 14 (9 ed., pp. 9616-9625). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38, No. 9). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v38i9.28818
Dehghanimohammadabadai, M., & Dayanikli, G. (2023). Enhancing Pandemic Preparedness Using Mean Field and Simulation Modeling. In 2023 Winter Simulation Conference, WSC 2023 (pp. 970-981). (Proceedings - Winter Simulation Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC60868.2023.10408053
Aurell, A., Carmona, R., Dayanıklı, G., & Laurière, M. (2022). Finite State Graphon Games with Applications to Epidemics. Dynamic Games and Applications, 12(1), 49-81. https://doi.org/10.1007/s13235-021-00410-2
Aurell, A., Carmona, R., Dayanikli, G., & Laurière, M. (2022). Optimal Incentives to Mitigate Epidemics: A Stackelberg Mean Field Game Approach: A STACKELBERG MEAN FIELD GAME APPROACH∗. SIAM Journal on Control and Optimization, 60(2), S294-S322. https://doi.org/10.1137/20M1377862
Carmona, R., Dayanıklı, G., & Laurière, M. (2022). Mean Field Models to Regulate Carbon Emissions in Electricity Production. Dynamic Games and Applications, 12(3), 897-928. https://doi.org/10.1007/s13235-021-00422-y