Surya Ganguli

Surya Ganguli is a professor of Applied Physics at Stanford, an Associate Director of Stanford’s Human Centered AI Institute, and a Venture Partner at General Catalyst. Dr. Ganguli triple majored in physics, mathematics, and EECS at MIT, completed a PhD in string theory at Berkeley, and a postdoc in theoretical neuroscience at UCSF. He has also been a visiting researcher at both Google and Meta AI, and a venture partner at a16z. His research spans the fields of AI, physics, and neuroscience, focusing on understanding and improving how both biological and artificial neural networks learn striking emergent computations. He has been awarded a Swartz-Fellowship in computational neuroscience, a Burroughs-Wellcome Career Award, a Terman Award, two NeurIPS Outstanding Paper Awards, a Sloan fellowship, a James S. McDonnell Foundation scholar award in human cognition, a McKnight Scholar award in Neuroscience, a Simons Investigator Award in the mathematical modeling of living systems, an NSF CAREER award, and a Schmidt Science Polymath Award.

AI2050 Project

Ganguli’s project seeks to advance a scientific foundation for explainable and trustworthy AI, uncovering the principles that govern how large generative and language models create, reason, and learn. His lab is developing analytic theories that mechanistically explain creativity and reasoning in systems such as diffusion models and large language models, revealing how these networks mix and recombine learned patterns to generate new ideas. Building on this framework, his group is also exploring new paradigms for reasoning in AI, connecting insights from neuroscience, control theory, and artificial intelligence to understand how models can recursively improve themselves through interaction and feedback. This work aims to illuminate the core principles underlying general intelligence, enabling the design of more interpretable, reliable, and human-aligned AI systems.