On 23 April 2026, Prof. ZHANG Jie, Chair Professor in Faculty of Business for Science and Technology, University of Science and Technology of China, delivered a PAIR Distinguished Lecture titled “Machine Listening: Extending AI from Vision to Sound and Vibration Sensing” at the PolyU campus. The lecture attracted almost 100 scholars, researchers and students onsite, and nearly 16,000 online viewers across various social media platforms to explore how the emerging field of “machine listening” is transforming urban monitoring, disaster prevention, and infrastructure safety.
Prof. Zhang opened the lecture by outlining the major challenges in today’s science and technology. He noted that while AI has reached significant maturity in visual perception, sound and vibration data remain “largely underutilised” in the digital era. He emphasised that machine learning in the domain of sound and vibration sensing is still at an early stage, with vast development potential ahead. While sharing technical insights, Prof. Zhang also reflected on his life and research journey. He remarked, “Only by fully committing myself and giving it everything I had did I discover how fascinating a discipline could be.” He emphasised that true excellence comes through continuous learning and self‑improvement. Technological innovation is now driven by cross‑disciplinary collaboration and collective progress, rather than individual heroism.
To illustrate how machine listening can be translated from concept to practice, Prof. Zhang presented several innovative real-world cases where sound sensing complements visual systems. Among them, he highlighted the “CitySeis” project in Hefei, where approximately 50,000 seismic sensors have been deployed to achieve citywide coverage, enabling continuous monitoring of subsurface structural changes and subway safety, and providing critical information beyond visual perception. He presented applications of “RoadSeis” in digital traffic systems and weight‑in‑motion sensing, showing how vibration signals can predict vehicle weight and assess road health. These examples demonstrated that machine listening can surpass visual technologies, offering a fuller picture of infrastructure conditions above and below ground.
The lecture concluded with a highly interactive Q&A session moderated by Prof. CHEN Jianli, Chair Professor of Space Geodesy and Earth Sciences. Discussions extended beyond technical theory to research ethics, societal impact, and cross‑disciplinary applications of machine listening, including smart ageing and home safety. Prof. Zhang shared his passion for lifelong scientific inquiry, while the session highlighted how AI can transcend visual limitations, opening new dimensions for research and industry.
Please click here for an online review.
| Topics | PAIR Distinguished Lecture Series |
|---|---|
| Research Units | PolyU Academy for Interdisciplinary Research |
Prof. ZHANG Jie
Member of U.S. National Academy of Engineering
Chair Professor in Faculty of Business for Science and Technology, University of Science and Technology of China
Prof. ZHANG Jie is a Chair Professor of the Faculty of Business for Science and Technology at the University of Science and Technology of China (USTC). He earned his BS from USTC (1986) and Ph.D. in from MIT (1996), and founded several high-tech companies. He received the STAR Award from the EPA (1994), the Reginald Fessenden Award from SEG (2012). In 2015, Fast Company ranked Dr. Zhang No. 1 on its list of the "100 Most Creative People in China." He has taught Geophysics at MIT, Stanford, and USTC. In 2020, he was elected to the United States National Academy of Engineering (NAE). Dr. Zhang has also served in several prestigious roles, including Vice President of SEG, member of MIT’s Visiting Committee, member of the Board of Governors at the Asia School of Business, and member of the SEG Foundation Board.
Personal website: https://faculty.ustc.edu.cn/zhangjie/en/index.htm
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