Friday, March 21, 2025
10:20 – 11:10 a.m. (CST)
ETB 1020
Xiongye Xiao
PhD Candidate , Dept. of Electrical & Computer Engineering
University of Southern California
Title: “AI for Science: From Microscopic Structures and Dynamics to Macroscopic Functions”
Abstract
The evolution of scientific discovery has transitioned from observational studies and mathematical modeling to data-driven AI methodologies. With the rapid advancement of deep learning and neural network architectures, AI has become a powerful tool for accelerating scientific discovery. However, as large-scale models exhibit emergent behaviors, understanding the structural and dynamic principles that govern these models is crucial.
In this talk, I will discuss Neuron-based Multifractal Analysis (NeuroMFA), a novel framework that bridges AI and scientific discovery by characterizing the self-organization of large models. Inspired by neuroscience, NeuroMFA provides a structural perspective on emergent intelligence in AI, offering insights into how deep neural networks develop complex functionalities. This approach enables a deeper understanding of AI’s role in science and facilitates advancements in areas such as material discovery, physics-informed machine learning, and computational neuroscience.
Biography
Xiongye Xiao is a researcher specializing in AI for Science, neural operators, and network science. He is a Ph.D. candidate in Electrical and Computer Engineering at the University of Southern California. His work focuses on developing advanced mathematical and machine learning frameworks to bridge microscopic structures and dynamics to macroscopic functions, with applications in neuroscience, material science, and AI-driven scientific discovery. He has published in leading venues such as NeurIPS, ICLR, and Science Robotics, and his contributions include pioneering Neuron-based Multifractal Analysis (NeuroMFA) for analyzing emergent intelligence in large models, as well as the Multiwavelet Neural Operator, which enhances PDE learning through multi-resolution representations.
Please join us on Friday, 3/21/25 at 10:20 a.m. in ETB 1020!
Xiongye Xiao’s Webpage: xiongyexiao.com
Google Scholar Page: https://scholar.google.com/citations?user=AvIxA64AAAAJ&hl=en&oi=ao
Host: Dr. Jiang Hu