Publications:8
Evan Schaffer, PhD
About Me
Dr. Evan Schaffer joined the Department of Neuroscience at the Friedman Brain Institute in 2023. His lab focuses on understanding the mechanisms and computational principles behind distributed signals in the brain and how neural representations change due to behavioral state and ongoing learning. The Schaffer lab uses mathematical and computational tools to explore the roles of proprioception and behavioral state in higher order cognitive processing and how they are impacted by psychiatric disorders.
Dr. Schaffer received his Ph.D. in Neurobiology from Columbia University in Dr. Larry Abbott’s Lab, where he studied the dynamics of recurrent neural networks. Dr. Schaffer completed his postdoctoral work in Dr. Richard Axel’s Lab at Columbia University. There, he developed network models to understand the consequences of random connectivity in the olfactory system and also developed novel methods to examine activity across the entire brain of behaving Drosophila. For more information, visit www.schafferlab.com.
Language
English
Position
ASSISTANT PROFESSOR | Neuroscience
Research Topics
Computational Biology, Computational Neuroscience, Neural Code, Neural Networks, Neuroscience, Systems Neuroscience, Theoretical Biology, Theoretical Neuroscience
Multi-Disciplinary Training Areas
Artificial Intelligence and Emerging Technologies in Medicine [AIET], Neuroscience [NEU]
Education
BA, Swarthmore College
PhD, Columbia University
Awards
2023
Simons Collaboration on the Global Brain Award
Research
Advances in many experimental techniques in neuroscience, spanning imaging, electrophysiological, and molecular tools, are enabling experimental access to questions that were impossible not long ago. Fully leveraging the potential of these experimental tools requires the accompanying development of new analysis methods. We are working with collaborators to address some of these challenges. Two areas of particular interest are identifying structure on multiple scales in large scale recordings and aligning datasets from multiple experimental modalities.
Publications
Selected Publications
- MULTI-MODAL GAUSSIAN PROCESS VARIATIONAL AU-TOENCODERS FOR NEURAL AND BEHAVIORAL DATA. Rabia Gondur, Usama Bin Sikandar, Evan S. Schaffer, Mikio Aoi, Stephen Keeley.
- The spatial and temporal structure of neural activity across the fly brain. Evan S. Schaffer, Neeli Mishra, Matthew R. Whiteway, Wenze Li, Michelle B. Vancura, Jason Freedman, Kripa B. Patel, Venkatakaushik Voleti, Liam Paninski, Elizabeth M.C. Hillman, L. F. Abbott, Richard Axel. Nature Communications
- Deep graph pose: A semi-supervised deep graphical model for improved animal pose tracking. Anqi Wu, E. Kelly Buchanan, Matthew R. Whiteway, Michael Schartner, Guido Meijer, Jean Paul Noel, Erica Rodriguez, Claire Everett, Amy Norovich, Evan Schaffer, Neeli Mishra, C. Daniel Salzman, Dora Angelaki, Andrés Bendesky, John Cunningham, Liam Paninski. Advances in Neural Information Processing Systems