Time: 15:00-16:00, 21 July 2025
Speaker: Ang Liu is an Associate Professor and doctoral supervisor in the School of Mechanical and Manufacturing Engineering at the University of New South Wales. He received his PhD in mechanical engineering from the University of Southern California in 2012. From 2013 to 2017, he was a young member of the International Academy for Production Engineering (CIRP). He was elected CIRP Associate Member in 2018 and Secretary of the CIRP Design Scientific Technical Committee in 2022. He was elected a Fellow of the PLuS Alliance in 2018, Senior Fellow of the Higher Education Academy in 2019, and ASME Fellow in 2022. He has chaired multiple international conferences and workshops and has delivered keynote speeches at international conferences and forums.
His teaching and research focus on design theory and methods, innovative design thinking, applications of digital twin technology in intelligent manufacturing, and international engineering education. Over the past five years, he has led multiple research projects in these areas. He has published two academic monographs and 130 papers in leading design and manufacturing journals and conferences, including CIRP Annals, ASME Transactions, and IEEE Transactions, with more than 11,000 Google Scholar citations. He has served as guest editor or editorial board member for ten well-known design and manufacturing journals and has edited proceedings for multiple international conferences. His honors include the 2021 UNSW Award for Teaching Excellence, the 2019 Park Best Journal Paper Award, selection by The Australian as one of 250 leading Australian researchers from 2021 to 2025 and the only selected scholar in manufacturing, and the 2022 Australian Awards for University Teaching.
Abstract:
This talk focuses on innovative applications of artificial intelligence in product development and intelligent manufacturing, covering multiple stages from conceptual design and virtual simulation to production process optimization. The talk will systematically explain how product development is shifting from traditional experience-driven design to a data-driven design paradigm centered on big data analytics and machine learning, and will use representative cases to demonstrate practical effects in improving efficiency, reducing costs, and optimizing quality. In addition, the talk will explore the social impacts, ethical challenges, and regulatory and standards requirements faced by responsible AI in intelligent design and manufacturing, and will propose feasible response strategies and practical recommendations.
