Yuzhen Qin

Radboud University, Nijmegen, Netherlands.

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Office: MM 02.364

Email: yuzhen.qin@ru.nl

I am a Tenure-Track Assistant Professor in the Department of Machine Learning and Neural Computing in Donders Institute for Brain, Cognition and Behaviour at Radboud University, the Netherlands. I am also a member of Dutch Brain Interface Initiative (DBI2), a multi-institude consortium.

I obtained my Ph.D. in Dec. 2019 from University of Groningen, the Netherlands, advised by Prof. Ming Cao. I received my M.E. from Wuhan University in 2015. From 2020 to 2023, I was a Postdoctoral Researcher with Prof. Fabio Pasqualetti with the Department of Mechanical Engineering at the University of California, Riverside.

Curent Research Topics

  • Modelling and Control for Brain Disorders Dynamics
  • Control of Complex Networks
  • Efficient Online Decision-Making (Reinforcement Learning and Bandits)
  • Data-Driven Control

News

Mar 7, 2025 Our paper has been accepted to IEEE ECC 2025.
Feb 5, 2025 I gave a talk on “vibrational control and epileptic modeling” to the Jan C. Willem Center for Systems and Control at the University of Groningen. It was a great pleasure to go back to Groningen. Thanks, Ming, for hosting me!
Jan 17, 2025 I gave a talk on “Towards Predictable Brain Stimulation for Epilepsy” to the Institute for System Analytics and Control (ISAC) at University of Kassel, Kassel, Germany. Thank Prof. Olaf Stursberg and Zonling for inviting me!
Dec 20, 2024 Our paper has been accepted to IEEE ICASSP.
Nov 22, 2024 I gave a talk on “Modeling and Control of Epilepsy” to the Utrecht-BCI lab, led by Prof. Nick F Ramsey. We had a wonderful discussion there!

Selected Publications

  1. Y. Qin, Y. Li, F. Pasqualetti, M. Fazel, and S. Oymak, Stochastic contextual bandits with long horizon rewards, Proceedings of the AAAI Conference on Artificial Intelligence, Feb 2023 arXiv Bib HTML
  2. Y. Qin, T. Menara, D. Bassett, and F. Pasqualetti, Phase-amplitude coupling in neuronal oscillator networks, Physical Review Research, Jun 2021 Bib HTML