Artificial intelligence is going far beyond just powering chatbots or image softwares and becoming a powerful tool for scientific research, helping us make sense of complex systems, discover new materials, and improve predictions in the natural world. In this talk, we’ll explore how AI is being used in three key areas of science.

First, we’ll look at how AI understands networks and graphs - structures that appear in everything from social systems to biology and traffic flow. Then we’ll explore how AI connects with topology, the mathematical study of shape and structure, to understand molecules, materials, and other complex data. Finally, we’ll examine physics-informed AI, where machine learning is combined with known scientific equations to build models that are both accurate and grounded in physical reality.

About Sanjukta Krishnagopal:

Sanjukta Krishnagopal is an assistant professor in the Computer Science department at UC Santa Barbara. She received her PhD in Physics from the University of Maryland where she was also a fellow of the Combine (Computational and Mathematics in Biological Networks) program. She was then a researcher at University College London, where she worked with Google DeepMind on computational models of cognition. She held a joint appointment at UC Berkeley and UCLA as a University of California Presidential Postdoctoral Fellow. Her research interests are multidisciplinary, with the goal of developing tools to answer questions about real world systems. She enjoys traveling to remote corners of the world and has lived on four continents. In her free time she enjoys dancing, diving and hiking.