I work at Anthropic on mechanistic interpretability of deep learning models. Previously, I did my PhD in the Center for Theoretical Neuroscience at Columbia University, advised by Ashok Litwin-Kumar, and my undergrad at Stanford in math and computer science. I've also worked on neuromotor interfaces at Meta, neuromorphic computing at Sandia National Labs, and optimizations for deep learning hardware at Cerebras Systems. I'm interested in a variety of topics in machine learning and neuroscience, including model interpretability, reinforcement learning, meta-learning, memory systems, and deep learning theory.


J. Lindsey, J. E. Markowitz, S. R. Datta, & A. Litwin-Kumar (2024). Dynamics of striatal action selection and reinforcement learning. bioRxiv. Link

M. Alleman*, J. Lindsey*, & Stefano Fusi (2024). Task structure and nonlinearity jointly determine learned representational geometry. ICLR 2024. Link

J. Lindsey* & S. Lippl* (2023). Implicit regularization of multi-task learning and finetuning in overparameterized neural networks. arXiv. Link

J. Lindsey & E.B. Issa (2023). Factorized visual representations in the primate visual system and deep neural networks. bioRxiv. Link

J. Lindsey & A. Litwin-Kumar. (2022). Theory of systems memory consolidation via recall-gated plasticity. bioRxiv. Link

J. Lindsey & A. Litwin-Kumar (2022). Action-modulated midbrain dopamine activity arises from distributed control policies. NeurIPS proceedings. Link

K. G. Mizes, J. Lindsey, G. S. Escola, & B. P. Ölveczky (2022). Dissociating the contributions of sensorimotor striatum to automatic and visually-guided motor sequences. bioRxiv. Link

J. Lindsey & J. B. Aimone (2022). Sequence Learning and Consolidation on Loihi using On-chip Plasticity. In Neuro-Inspired Computational Elements Conference (pp. 70-72). Link

K. G. Mizes, J. Lindsey, G. S. Escola, & B. P. Ölveczky (2022). Similar striatal activity exerts different control over automatic and flexible motor sequences. bioRxiv. Link

G. Chen, B. Kang, J. Lindsey, S. Druckmann,, & N. Li. (2021). Modularity and robustness of frontal cortical networks. Cell, 184(14), 3717-3730. "Modularity and robustness of frontal cortical networks." Cell 184.14: 3717-3730. Link

F. Li, J. Lindsey, E. C. Marin, N. Otto, M. Dreher, G. Dempsey, I. Stark, A. S. Bates, M. W. Pleijzier, P. Schlegel, A. Nern, S. Takemura, N. Eckstein, T. Yang, A. Francis, A. Braun, R. Parekh, M. Costa, L. K. Scheffer, Y. Aso, G. S. X. E. Jefferis, L. F. Abbott, A. Litwin-Kumar, S. Waddell & G. M. Rubin (2020). The connectome of the adult Drosophila mushroom body provides insights into function. eLife 9: e62576. Link

J. Lindsey & A. Litwin-Kumar (2020). Learning to Learn with Feedback and Local Plasticity. NeurIPS proceedings. Link

J. Lindsey*, S. Ocko*, S. Ganguli, & S. Deny (2019). A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs. ICLR proceedings (oral presentation). Link

S. Ocko*, J. Lindsey*, S. Ganguli, & S. Deny (2018). The Emergence of Multiple Retinal Cell types through Efficient Coding of Natural Movies. NeurIPS proceedings. Link

M. Jain & J. Lindsey (2018). A Neural Network Model of Complementary Learning Systems. CogSci 2018 proceedings (oral presentation). Link

M. Jain & J. Lindsey (2018). Semiparametric Reinforcement Learning. ICLR, Workshop Track. Link

J. Lindsey (2017). Pre-Training Attention Mechanisms. NeurIPS 2017 Workshop on Cognitively Informed Artificial Intelligence. Link