Dynamical Intelligence Group (DIG)

Research Group @ Johns Hopkins University Electrical and Computer Engineering Department

JHU_pic.jpg

DIG is an interdisciplinary group of researchers and students who are interested in understanding the dynamics of learning and the learning of dynamics in artificial and biological systems. We work in the intersection of dynamical systems and control theory, machine learning, and neuroscience.

news

Apr 23, 2026 DIG is excited to have been awarded an International Brain Research Organization (IBRO) Collaborative Research Grant funded to expand our collaboration with Prof. Roberto Bottini’s group (University of Trento)! We appreciate the support.
Mar 28, 2026 New preprint out on using Koopman operator theory for characterizing reinforcement learning behavior: Interpreting Reinforcement Learning Model Behavior via Koopman with Control !
Mar 12, 2026 DIG is very excited to have Edouard de Ponnat joining us in the Fall as an ECE graduate student - welcome Edouard!
Dec 19, 2025 New preprint out on grid cell computation: Distance by de-correlation: Computing distance with heterogeneous grid cells. A great collaboration with Priti Dasbehera and Akshunna S. Dogra!

selected publications

  1. Chaos
    Koopman learning with episodic memory
    William T. Redman, Dean Huang, Maria Fonoberova, and 1 more author
    Chaos: An Interdisciplinary Journal of Nonlinear Science, 2025
  2. NeurIPS
    Identifying equivalent training dynamics
    William T. Redman, Juan Bello-Rivas, Maria Fonoberova, and 3 more authors
    Advances in Neural Information Processing Systems, 2024
  3. NeurIPS
    Not so griddy: Internal representations of RNNs path integrating more than one agent
    William T. Redman, Francisco Acosta, Santiago Acosta-Mendoza, and 1 more author
    Advances in Neural Information Processing Systems, 2024