Professor Maryam Kamgarpour

Research Interest:

  • Optimization
  • Learning
  • Multi-agent systems and control

Biography

Maryam Kamgarpour is a professor in the School of Engineering of École Polytechnique Fédérale de Lausanne. Prior to EPFL, she served as a faculty at the University of British Columbia and at ETH Zürich. She holds a Doctor of Philosophy in Engineering from the University of California, Berkeley and a Bachelor of Applied Science from University of Waterloo, Canada. Her research is on stochastic control and multiagent learning and control. Her theoretical research is motivated by control problems arising in intelligent transportation systems, robotics, and power grid systems.

She was awarded the European Union Starting Grant (2016-2021) to advance her research on control and game theory for integrating renewable energy into the power system. Her work on distributed control received the IEEE Transactions on Control of Network Systems Outstanding Paper Award (2022). She collaborated with NASA on safe and fuel-efficient aircraft trajectory design, and for this work received the NASA High Potential Individual Award (2010).

She is passionate about understanding and addressing fundamental control problems at the intersection of engineering, mathematics and computer science, and in mentoring students to work with her on these problems. Her publications have contributed to theory of hybrid systems (reachability, safety and optimal control), distributed control (the role of information structure), game theory (learning equilibria under bandit feedback), mechanism design (coalition-proofness, price of anarchy), safe zeroth-order learning, inverse reinforcement learning and multiagent reinforcement learning. 

 

Publications (most recent)

Informed scenario-based RRT∗ for aircraft trajectory planning under ensemble forecasting of thunderstorms

E. Andrés; D. González-Arribas; M. Soler; M. Kamgarpour; M. Sanjurjo-Rivo 

Transportation Research Part C: Emerging Technologies. 2021. Vol. 129, p. 103232. DOI : 10.1016/j.trc.2021.103232.

Bandit Online Learning of Nash Equilibria in Monotone Games

T. Tatarenko; M. Kamgarpour 

2021

A market-based approach for enabling inter-area reserve exchange

O. Karaca; S. Delikaraoglou; M. Kamgarpour 

Operations Research Letters. 2021. Vol. 49, num. 4, p. 501-506. DOI : 10.1016/j.orl.2021.05.009.

Multi-robot task allocation for safe planning against stochastic hazard dynamics

D. Tihanyi; Y. Lu; O. Karaca; M. Kamgarpour 

2021-05-25

Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid

O. Karaca; D. Tihanyi; M. Kamgarpour 

Operations Research Letters. 2021. Vol. 49, num. 6, p. 855-861. DOI : 10.1016/j.orl.2021.09.006.

Contact

e-mail address: [email protected]


+41 21 693 57 30


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