I’m currently a Swartz postdoctoral fellow for computational neuroscience in University of Washington, mentored by Dr. Eric Shea-Brown. Previously, I got my PhD from University of California, San Diego under the supervision of Dr.Terrence Sejnowski at Salk. My research focuses on revealing latent varibles via network learning theories and Bayesian inference methods. I mainly work with foraging tasks ranging from random walks to social collaborative foraging.

Besides lab research, I’m broadly interested in AI algorithms, theories and puzzles. During the years, I accumulated pages of research notes (network dynamics, causality estimation, ICA algorithms) and side projects (Object recognition, SLAM, puzzle sovling!) and equivalently two M.S. degrees!

I’m posting them here so that they don’t have to go through the painful and lengthy review process to qualify as publications. If anyone is interested in these material, feel free to drop me an email (cyusi@uw.edu).

Latest Publication

• Yusi Chen, Huanqiu Zhang, Mia Cameron and Terrence J. Sejnowski, Hippocampus as a generative circuit for predictive coding of future sequences. (2024) Accepted to Neuron. [paper]

• Yusi Chen, Burke Q. Rosen and Terrence J. Sejnowski, Dynamical differential covariance recovers directional network structure in multiscale neural systems. Proceedings of the National Academy of Sciences (2022). [paper][code] [5-min video]
  • Our ability to think, feel, and react depends on the underlying interaction patterns of distinct brain regions. This paper defines the interaction patterns in a dynamical system and derived an efficient algorithm to estimate it from time-series data.

• Yusi Chen, Qasim Bukhari, Tiger W. Lin, Terrence J. Sejnowski; Functional connectivity of fMRI using differential covariance predicts structural connectivity and behavioral reaction times. Network Neuroscience 2022; [paper]

• All publications

Fun Projects

• Simultaneous Localization and Mapping (SLAM)
  • Core question in autonomous driving: how to represent the street map and self location with information from in-vehicle cameras and kinetic data (e.g. linear/angular velocity). Following are two Bayesian filters transforming visual/kinetic streams into latent variable series representing the map and location
  • Particle Filter: [code] [report]
  • Unscented Kalman Filter: [code] [report]
• Image Classification through neural networks: [code]
• Seahorse puzzle: [code]
  • Nine square tiles to place in a 3-by-3 grid
  • Around 100 billion possibilities with different positions and poses
  • Only ONE possibility to match all patterns on the edges

Notes

• Mathematical models for oscillatory signals in the brain
  • [Where does it arise from?]
  • [Why do they oscilate?]
• The past and future of Dynamical Differential Covariance (DDC)
  • [Theoretical foundations of differential covariance]
  • [Other potential DDC variants]
• The many algorithms of ICA
  • Real-valued ICA: infomax, FastICA, et al. [note] [code]
  • Complex-valued ICA: how to extend definitions to the complex field and translate it back to real-valued ICA. [note] [code]

Recommended Courses

• Probability Theory
  • by Prof. Todd Kemp from UCSD Mathematics
  • one-year sequence of courses to define probability concepts from the sample space
• Modern Physics
  • by Prof. Leonard Sussikind from Stanford
  • multiple lecture sequences introducing classical mechanics, quantum mechanic, et al.
• Robotics
  • by Prof. Nikolay Atanasov from UCSD Engineering
  • a clear and straightforward introduction of cutting-edge robotic algorithms.
• Information Theory
  • by Prof. Alon Orlitsky from UCSD Engineering
• Computational Neuroscience
  • by Prof. Terrence Sejnowski from Salk (Yes, my PI)
  • for whoever wants to know about computational neuroscience.

Service

• Reviewer for Proceedings of the National Academy of Sciences
• Reviewer for Neural Computation
• Graduate instructor assistant for system computational neuroscience, UCSD
• Graduate instructor assistant for bioinformatics, UCSD

Awards

• Kavli-Helinski Fellowship (08/2021)
• National Scholarship of China (2016)