Date：2026/4/1 15:30-17:00
Location：R101, CSIE
Speakers：Dr. Jeng-Lin Li 李政霖
Host：羅紹元教授
Abstract:
Manufacturing workflows demand reliability under conditions of complexity, variability, and scale. Persistent challenges such as anomaly detection in production lines, accurate physics simulation for process modeling, and adaptive control of robotic arms highlight the need for robust optimization strategies. Artificial intelligence is transforming these challenges into insights by enabling predictive monitoring, simulation-driven design, and autonomous decision-making. This talk explores how AI techniques can enhance workflow reliability in manufacturing. We will examine how large language models and multi-agent systems orchestrate tasks across diverse environments, how simulation-based AI improves precision, and how explainable AI ensures transparency in critical operations. By bridging theory with real-world manufacturing projects, the session demonstrates how AI not only optimizes workflows but also redefines reliability as a driver of innovation. Attendees will gain practical perspectives on applying AI to industrial contexts, preparing them to design workflows that thrive in dynamic, high-stakes environments.
Biography:
Jeng-Lin (John) Li is currently Director of the AI Research Center at Inventec Corporation and an Adjunct Assistant Professor in the Biomed AI PhD program at National Tsing Hua University (NTHU). He also serves as an Industrial Instructor at National Taiwan University of Science and Technology. He received his Ph.D. (2022) degree from the Department of Electrical Engineering at NTHU. He was a technical advisor at the medical AI startup AHEAD Medicine Inc. His research interests are machine learning, reliable AI, multimodal processing, health analytics, and affective computing.