Yuquan Meng has successfully defended his doctoral dissertation titled “Physics-Informed Machine Learning for Smart Decision-Making in Ultrasonic Metal Welding.” The defense was conducted before an esteemed Examination Committee consisting of Prof. Chenhui Shao, Prof. Placid Ferreira, Prof. Srinivasa Salapaka, and Prof. Pingfeng Wang.
In his research, Yuquan Meng has made significant contributions to the field of ultrasonic metal welding by integrating physics-based knowledge with machine learning techniques. His work focuses on developing advanced algorithms and models that leverage the power of data-driven approaches while incorporating the human knowledge of ultrasonic metal welding. By combining physics and machine learning, Yuquan Meng’s research aims to enhance the decision-making process in this important manufacturing process.
Following his successful doctoral defense, Yuquan Meng will continue his academic journey as a post-doctoral researcher at the Automation and Digital Manufacturing Lab at UIUC. In this role, he will further contribute to the advancement of knowledge in the field of smart manufacturing and continue his exploration of the applications of physics-informed machine learning in ultrasonic metal welding.
Congratulations to Yuquan!