Pehlevan Group
Our goal is to elucidate the theoretical foundations of natural and artificial intelligence through the lens of neural computation. Our research intersects with theoretical and computational neuroscience, deep learning theory, the physics of learning, machine learning, statistical mechanics and high-dimensional statistics. We are particularly interested in how computation emerges in neural networks through the collective dynamics of simple processing units, or neurons. By uncovering these dynamics, we aim to understand the capabilities and limitations of intelligent systems across various contexts, informing future innovations in machine learning and neurotechnology.
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Affiliations
John A. Paulson School of Engineering and Applied Sciences
Center for Brain Science
Kempner Institute for the Study of Natural & Artifical Intelligence
Simons Collaboration on the Physics of Learning and Neural Computation
Swartz Program in Theoretical Neuroscience
Center of Mathematical Sciences and Applications
Harvard Machine Learning Theory
Harvard Data Science Initiative
Neurotheory
Program in Neuroscience
The Biophysics Program
Harvard Brain Science Initiative
The Mind Brain Behavior Interfaculty Initiative
The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (…