Yuzhen Qin
 |
Tenure-Track Assistant Professor |
Short Biography
Since Mid-September 2023, I have been a tenure-track assistant professor at Radboud University. As a member of the multi-institude consortium DBI2, backed by a substantial 10-year grant totaling 21.9M Euros, I do not have to teach in the initial 3 years. Thus, You may call me a researcher.
From Jan. 2020 to Jul. 2023, I was a postdoctoral researcher at the University of California, Riverside, advised by Prof. Fabio Pasqualetti.
In Dec. 2019, I obtained my Ph.D. degree from University of Groningen. My advisor was Prof. Ming Cao.
Before that, I did my master in Wuhan University, China.
Research Interests
My research mainly aims to develop brain-inspired efficient, adaptive, and autonomous learning and decision-making models. Toward this goal, I build network systems to reveal the fundamental principles underlying the brain's efficiency, adaptability, and autonomy in integrating and processing information from a lens of control theory and dynamical systems. As a complementary goal, I also leverage tractable control systems design to inform mechanistic and predictable therapeutics for neurological disorders.
News
Sep. 16: I started a new position as an assistant professor at the Department of Artificial Intelligence in the Donders Institute for Brain, Cognition and Behaviour at Radboud University, the Netherlands. Thanks to the substantial grant DBI2 (Dutch Brain Interface Initiative), I do not have to teach in the first 3 years. You can simply call me a researcher.
Feb. 16: I gave a talk on “Stochastic Contextual Bandits with Long Horizon Rewards” at ITA 2023.
Feb. 9: I gave a talk on “Stochastic Contextual Bandits with Long Horizon Rewards” (PDF) at AAAI 2023.
Jan: Our ACC paper “Vibrational Stabilization of Complex Network Systems” has been accepted to ACC 2023! Paper coming soon.
Nov 11: Our paper “Stochastic Contextual Bandits with Long Horizon Rewards” has been accepted to AAAI 2023! The acceptance rate this year is 19.6%. Paper coming soon.
Sep 30: We submitted a paper entitled “Vibrational Stabilization of Complex Network Systems” to ACC 2023.
Aug 18: We submitted a paper entitled “Stochastic Contextual Bandits with Long Horizon Rewards” to AAAI 2023 conference.
Jul 15: Both papers are accepted to CDC 2022.
Jun 16: I gave a talk on Representation Learning in Sequential Decision-Making in the Department of Engineering at the University of Cambridge.
May: Our paper entitled “Non-Stationary Representation Learning in Sequential Linear Bandits” has been accepted to the IEEE Open Journal of Control Systems.
March: We submitted two papers to the 2022 Conference on Decision and Control (CDC):
“Flexible Information Propagation in Oscillator Networks”;
“Vibrational Control of Cluster Synchronization: Connections with Deep Brain Stimulation”.
January: Our paper entitled “Representation Learning for Context-Dependent Decision-Making” has been accepted to the 2022 American Control Conference (ACC).
January: We submitted our paper entitled “Non-Stationary Representation Learning in Sequential Linear Bandits” to the IEEE Open Journal of Control Systems.
October: We submitted our paper entitled “Representation Learning for Context-Dependent Decision-Making” to the 2022 American Control Conference (ACC).
Septermber: Our paper entitled “Partial exponential stability analysis of slow-fast systems via periodic averaging” has been accepted by IEEE Transactions on Automatic Control.
July: I presented a poster on our work “Non-stationary representation learning in sequential multi-armed bandits” at ICML 2021 Workshop on Reinforcement Learning Theory.
May: our paper entitled “Phase-amplitude coupling in neuronal oscillator networks” has beed accepted by Physical Review Research.
February: Our paper entitled “Partial Phase Cohesiveness in Networks of Networks of Kuramoto Oscillators”, now available in early access of IEEE Transactions on Automatic Control.