Time: 09:00–11:00, May 25, 2026

Venue: Room 335, Building 2H, Science Park

Lecture Topic: Machine Listening: Extending Artificial Intelligence from Visual Perception to Acoustic and Vibration Perception

Speaker Profile

Jie Zhang serves as a Chair Professor at Faculty of Business for Science & Technology, University of Science and Technology of China, and a member of the National Academy of Engineering of the United States. His research and industrial transformation endeavors span geophysics, artificial intelligence-based acoustic listening, and urban safety monitoring. He has published more than 220 academic papers, holds 40 patents, and led the research and development of over 20 technological products. He earned his bachelor’s degree from the University of Science and Technology of China in 1986 and his Doctor of Philosophy (Ph.D.) from the Massachusetts Institute of Technology (MIT) in 1996. Starting in 1998, he founded multiple high-tech enterprises in the United States. Since 2009, he has held faculty position at MIT, Stanford University, and the University of Science and Technology of China. He has received numerous awards, including the Presidential Early Career Award for Scientists and Engineers issued by the president of the United States, and the Reginald Fessenden Award for Technical Achievement from the Society of Exploration Geophysicists (SEG). In 2015, he ranked first on Fast Company’s list of the 100 Most Creative People in Chinese Business. In 2020, he was elected a member of the U.S. National Academy of Engineering for his contributions to advancing seismology, exploration geophysics, and medical science. He previously served as First Executive Vice President of SEG, a member of the MIT Steering Committee, and Executive Director of MIT Asia Business School. He currently, serves on the Board of Directors of the SEG Foundation.

Lecture Abstract

This lecture centers on Machine Listening, a cutting-edge research area that extends artificial intelligence beyond visual perception to acoustic and vibration perception. Subject to fundamental physical laws, all mechanical movements, structural transformations and energy exchanges generate acoustic and vibration signals, yet audio and vibration data remain vastly underutilized to date. This lecture compares the perceptual characteristics and data volume gaps between human vision and hearing, and introduces machine listening technology capable of capturing and analyzing airborne sound, fluid-borne sound and solid-medium vibration signals to build an integrated air-ground-underground real-time monitoring system. Combined with advances in large language models, it analyzes the application potential of machine listening in urban environmental monitoring, resource exploration, safety early warning and other sectors, offering innovative insights for technological breakthroughs in multi-modal perception and intelligent monitoring.