Eduardo Sebastián
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InfoPhD Candidate ContactOffice: Lab. 1.01, Ada Byron Building, Calle María de Luna 3, Zaragoza, Spain, 50018 |
Biography
I am a Ph.D. student in the Perception-Oriented Control Team, part of the Robotics, Perception and Real-Time Group at the Departamento de Informática e Ingeniería de Sistemas and Instituto de Investigación en Ingeniería de Aragón, Universidad de Zaragoza. My advisors are Prof. Eduardo Montijano and Prof. Carlos Sagüés. I received the B.Eng. in Electronic and Automatic Engineering (Hons, 1st rank) and the M.Eng. in Electronics (Hons, 1st rank) from the Universidad de Zaragoza in 2019 and 2020 respectively. My research is funded by a FPU national grant (1st rank), the highest personal grant offered by the Spanish Government for Ph.D. candidates. I visited the Existential Robotics Laboratory supervised by Prof. Nikolay A. Atanasov from April-2022 to August-2022 and from May-2024 to November-2024. I am a Fulbright Scholar and a DAAD AInet Fellow.
Research Interests
I'm open for any amazing topic related to robotics, networked system, control and learning, and, occasionally, power electronics.
News
Nov 2024 I have been selected as a DAAD AInet fellow on AI for Science.
Oct 2024 I gave a talk at Cornell University (on Halloween!).
Oct 2024 I am attending DARS'24 at New York!
Oct 2024 I submitted my PhD dissertation :) .
Oct 2024 I gave a talk at the ProrokLab, University of Cambridge.
July 2024 New paper presenting AVOCADO, an adaptive and optimal collision avoidance method driven by opinion.
June 2024 I am attending CVPR'24 at Seattle!
May 2024 Our paper, presenting an automatic and data-driven method for power losses estimation in power converters, has been accepted for publication at IEEE Transactions on Power Electronics.
May 2024 Our paper, presenting the fastest distributed first order optimization method up to date, has been accepted for publication at IEEE Control Systems Letters.
Mar 2024 Two new papers submitted: the first one solves, for the first time, the problem of distributed discrete-time dynamic outer approximation of the intersection of ellipsoids and the second one proposes the fastest distributed first order optimization method up to date.
Jan 2024 Our new paper on Physics-Informed Multi-Agent Reinforcement Learning for Distributed Multi-Robot Problems is available for reading and open for discussion!.
Nov 2023 Our ECO-DKF paper, presenting the first event-triggered and certifiable optimal distributed Kalman filter, has been accepted for publication at IEEE Transactions on Automatic Control.