Sotabase

Career

· Assistant Professor of Physics and of Applied Mathematics, Harvard University2025–
· Postdoctoral Fellow, Center for Theoretical Neuroscience, Columbia University
· B.A. in Mathematics and Physics, Cornell University
· Project Leader, Center for Computational Neuroscience, Flatiron Institute, Simons Foundation
· Ph.D. in Applied Physics, Harvard University
· BCS Fellow in Computation, Massachusetts Institute of Technology (MIT)
· Assistant Professor of Neural Science, New York University

Publications (62)

Neural population geometry: An approach for understanding biological and artificial neural networks
Current Opinion in Neurobiology · 2021
256
cited
Separability and geometry of object manifolds in deep neural networks
Nature Communications · 2019
241
cited
Classification and Geometry of General Perceptual Manifolds
Physical Review X · 2017
174
cited
On the geometry of generalization and memorization in deep neural networks
International Conference on Learning Representations · 2021
89
cited
25th Annual Computational Neuroscience Meeting: CNS-2016
BMC Neuroscience · 2016
84
cited
Emergence of Separable Manifolds in Deep Language Representations
International Conference on Machine Learning · 2020
46
cited
Neuroscience needs Network Science
arXiv.org · 2023
45
cited
Linear readout of object manifolds.
Physical Review E · 2015
43
cited
Untangling in Invariant Speech Recognition
Neural Information Processing Systems · 2020
34
cited
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations
Neural Information Processing Systems · 2023
33
cited
Credit Assignment Through Broadcasting a Global Error Vector
Neural Information Processing Systems · 2021
27
cited
On 1/n neural representation and robustness
Neural Information Processing Systems · 2020
27
cited
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception
Neural Information Processing Systems · 2021
26
cited
A Spectral Theory of Neural Prediction and Alignment
Neural Information Processing Systems · 2023
19
cited
Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models
Workshop on Representation Learning for NLP · 2021
19
cited
Divisive Feature Normalization Improves Image Recognition Performance in AlexNet
International Conference on Learning Representations · 2022
14
cited
Learning Data Manifolds with a Cutting Plane Method
Neural Computation · 2017
14
cited
Small Molecule Injection into Single-Cell C. elegans Embryos via Carbon-Reinforced Nanopipettes
PLoS ONE · 2013
13
cited
Linear Classification of Neural Manifolds with Correlated Variability
Physical Review Letters · 2022
12
cited
Transformation of acoustic information to sensory decision variables in the parietal cortex
bioRxiv · 2022
11
cited
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SueYeon Chung | Researcher Profile | Sotabase | Sotabase