William Redman

The DYNS Experience

The aspect of DYNS that most made me want to come to UCSB was the ability to work in a cutting-edge systems neuroscience lab, while at the same time continuing my education in physics and math, and I sure got everything (and more) that I bargained for. Working in the Goard Lab gave me a real detailed understanding of neurophysiology and the opportunity to develop novel tools for recording from the hippocampus circuit. Flexible choice of courses let me take advanced coursework in dynamical systems theory, allowing me to be at the forefront of using tools from Koopman operator theory to study machine learning systems. I can’t imagine a richer academic environment for my PhD! 

Published as a Graduate Student

9. E. R. J. Levy, S. Carrillo-Segura, E. H. Park, W. T. Redman, J. Hurtado, S. Y. Chung, A. A. Fenton, "A manifold neural population  code for space in hippocampal coactivity dynamics independent of place fields''. (Accepted) Cell Reports (2023)

8. W. T. Redman, M. Fonoberova, R. Mohr, I.G. Kevrekidis, and I. Mezić, "Algorithmic (Semi-)Conjugacy via Koopman Operator  Theory''. IEEE Conference on Control and Decision (CDC 2022)

7. W. T. Redman, et al., "Long-term Transverse Imaging of the Hippocampus with Glass Microperiscopes''. eLife (2022)

6. W. T. Redman, T. Chen, Z. Wang, and A. S. Dogra, "Universality of Winning Tickets: A Renormalization Group Perspective''.  International Conference on Machine Learning (ICML 2022) 

5. W. T. Redman, M. Fonoberova, R. Mohr, I.G. Kevrekidis, and I. Mezić, "An Operator Theoretic View on Pruning Deep Neural  Networks''. International Conference on Learning Representations (ICLR 2022) 

4. W. T. Redman, "On Koopman Mode Decomposition and Tensor Component Analysis''. Chaos (2021)

3. A. S. Dogra* and W. T. Redman*, "Optimizing Neural Networks via Koopman Operator Theory''. Advances in Neural Information  Processing Systems (NeurIPS 2020)

2. W. T. Redman, "Renormalization group as a Koopman operator''. Physical Review E  (2020) 

1.  W. Redman, "An O(n) method of calculating Kendall correlations of spike trains''. PLOS ONE (2019)

Post PhD

I am currently (as of 09/2023) a Senior Research Scientist at Johns Hopkins Applied Physics Lab, in the Intelligent Systems Center, broadly working on neuroscience inspired AI, computational neuroscience, machine learning for multi-agent systems, dynamical systems theory, and robotics.