Jack Lindsey

  • Program Year: 1
  • Academic Institution: Columbia University
  • Field of Study: Computational Neuroscience
  • Academic Advisor: Ken Miller
  • Practicum(s): Practicum Not Yet Completed
  • Degree(s):
    B.S. Mathematics, and M.S. Computer Science, Stanford University, 2019
  • Personal URL: http://jackwlindsey.com


A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs. Lindsey, J.*, Ocko, S.*, Ganguli, S., and Deny, S. International Conference on Learning Representations, 2019. https://openreview.net/pdf?id=S1xq3oR5tQ

The Emergence of Multiple Retinal Cell types through Efficient Coding of Natural Movies. Ocko, S.* Lindsey J.*, Ganguli, S., Deny, S. Advances in Neural Information Processing Systems, 2018. https://www.biorxiv.org/content/early/2018/10/31/458737

A Neural Network Model of Complementary Learning Systems. Jain, M* and Lindsey, J*. CogSci 2018 proceedings. http://mindmodeling.org/cogsci2018/papers/0118/0118.pdf.

Semiparametric Reinforcement Learning. Jain, M* and Lindsey, J*. International Conference on Learning Representations, Workshop Track, 2018. https://openreview.net/pdf?id=B1LRWg1wz.

Pre-Training Attention Mechanisms. Lindsey, J*. Neural Information Processing Systems 2017 Workshop on Cognitively Informed Artificial Intelligence. https://arxiv.org/abs/1712.05652.


Stanford J.E. Wallace Sterling Award for Scholastic Achievement, 2019

Stanford Dean's Award for Academic Achievement, 2019

Rhodes Scholarship finalist, 2018

Stanford Bio X Summer Fellowship, 2018

President's Award for Academic Excellence in the freshman year, 2016

Nominee, Boothe Prize for excellence in writing, 2016

National Merit Scholarship Winner, 2015