I am Po-Chen Kuo, a 3rd-year Ph.D. Candidate studying computational neuroscience at University of Washington and a visiting scientist at the Allen Institue for Neural Dynamics. I am fortunate to have Professor Edgar Y. Walker as my advisor, and work closely with the UW Computational Neuroscience Center. Previously I received my M.D. and B.Sc. in Physics at National Taiwan University in 2020.
I am interested in how neural circuits, dynamics, and computation support the complex phenomena of cognition, behavior, and intelligence in organmisms. I study how biological and artificial intelligent systems adapt under uncertainty, with a focus on reinforcement learning, Bayesian inference, and meta-learning. Please visit my research page for more details!
Aside from research, I enjoy reading, cooking, and baseball.
Email: pckuo [at] uw [dot] edu
Office: Magnuson Health Sciences Building, 1705 NE Pacific Street, Seattle, WA 98195
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems. Brenner, M., Hess, F., Mikhaeil, J. M., Bereska, L. F., Monfared, Z., Kuo, P.-C., & Durstewitz, D. Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2292-2320, 2022.
Self-similarity student for partial label histopathology image segmentation. Cheng, H.-T., Yeh, C.-F., Kuo, P.-C., Wei, A., Liu, K.-C., Ko, M.-C., … & Liu, T.-L. European Conference on Computer Vision (pp. 117-132). Springer, Cham. 2020.
[Upcoming, Aug 2024] Cognitive Computational Neuroscience 2024 (Poster, Paper) “Adaptive Learning Under Uncertainty With Variational Belief Deep Reinforcement Learning” Kuo, P.-C., Hou, H., & Walker, E. Y.
[Upcoming, Jun 2024] AREADNE 2024, Research in Encoding And Decoding of Neural Ensembles (Poster, Abstract) “An information-theoretical approach to optimize task design for distinguishing probabilistic codes in neural populations” Kuo, P.-C. and Walker, E. Y.
[May 2024] CoNectome 2024 Symposium (Poster, Abstract) “Bayesian reinforcement learning for the computational basis of dynamic foraging” Kuo, P.-C. and Walker, E. Y.
[Mar 2024] Hendrickson Trainee Symposium, University of Washington School of Medicine (Poster, Abstract) “Bayesian reinforcement learning for the computational basis of dynamic foraging” Kuo, P.-C. and Walker, E. Y.
[Feb 2024] Janelia Conference, Bridging Diverse Perspectives on the Mechanistic Basis of Foraging (Poster, Abstract) “Bayesian reinforcement learning as a mechanistic model for dynamic foraging behavior” Kuo, P.-C. and Walker, E. Y.
[Feb 2024] University of Washington, NEUSCI 403 Lecture (Computational Models For Cognitive Neuroscience). “Adaptive learning under uncertainty: learning to reinforcement learn with actor-critic recurrent neural networks”
[Aug 2023] Allen Institute for Brain Science, Summer Workshop on the Dynamic Brain. “What gives rise to neural variability and dynamics?”