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Faculty Search Research Seminar: Chenhui Shao
March 16, 2023 @ 11:00 am - 12:00 pm
ME Faculty Candidate Seminar:
“Cost-Effective Machine Learning for Smart Manufacturing”
Associate Professor
University of Illinois at Urbana-Champaign
Thursday, March 16, 2023, 11:00 am
2540 ME Grand Conference Room
GG Brown Building
Abstract:
Machine learning plays a pivotal role in smart manufacturing by powering a variety of decision-making tasks. Because machine learning essentially learns from data, the “cost of data” accounts for an ever-increasing proportion of the “cost of decision-making” in modern manufacturing. Furthermore, while conventional machine learning methods have proven to be highly effective in “learned” settings, they may not be readily scalable or generalizable to complicated, rapidly evolving production environments. The cost-prohibitive nature of manufacturing data together with the lack of scalability and generalizability have become critical barriers to the widespread adoption of machine learning on the factory floor. Cost-effective machine learning—a new paradigm featured by efficiency, scalability, generalizability, and responsiveness—holds significant potential for overcoming these barriers. This talk will present a suite of enabling methodologies including sampling design (aka active learning), transfer learning, domain adaptation and generalization, and federated learning that span the full life cycle of data-driven decision-making. Real-world case studies involving a wide range of manufacturing applications (e.g., additive manufacturing, micro-and nano-scale two-photon lithography, ultrasonic metal welding, high-precision machining) will be discussed to illustrate these methodologies and demonstrate their effectiveness in various decision-making tasks such as part qualification, online monitoring, maintenance, fault diagnosis, and quality improvement.
Bio:
Dr. Chenhui Shao is an Associate Professor in the Department of Mechanical Science and Engineering, the Mechanical Engineering Director of ZJUI Education Programs, and an affiliate faculty member of the Institute for Inclusion, Diversity, Equity & Access (IDEA) at the University of Illinois at Urbana-Champaign. Chenhui received his B.E. degree in Automation from the University of Science and Technology of China; M.S.E. degree in Industrial and Operations Engineering, M.A. degree in Statistics, and Ph.D. degree in Mechanical Engineering, all from the University of Michigan, Ann Arbor. His research interests focus on smart manufacturing, machine learning, statistics, materials joining, and manufacturing systems control and automation. Chenhui’s honors and awards include NSF CAREER Award, ASME Chao and Trigger Young Manufacturing Engineer Award, IISE Manufacturing and Design (M&D) Division Outstanding Young Investigator Award, SME Barbara M. Fossum Outstanding Young Manufacturing Engineer Award, SME 30 Under 30 Honoree, and Dean’s Award for Excellence in Research at Illinois. His research contributions have been recognized by multiple best paper awards and the Manufacturing USA Report. In 2021, Chenhui was selected as one of 30 nationwide to attend the ASEE DELTA Junior Faculty Institute. He is routinely named to UIUC’s List of Teachers Ranked as Excellent by Their Students. Chenhui currently serves as an associate editor of the Journal of Manufacturing Processes.