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Keynote Speakers

Dr. Birgit Vogel-Heuser

Biography:
Birgit Vogel-Heuser received her Dipl. Ing. degree in electrical engineering in 1987 and her Dr.-Ing. degree in mechanical engineering in 1990 from the RWTH Aachen, Germany. She acquired over ten years industrial experience in industrial automation. After different professorship positions, she was appointed to the Chair of Automation and Information Systems at the Technical University Munich in 2009. Her research is focussing on evolvable field-level automation and appropriate architectures for manufacturing and logistic systems. She is a Senior Member of the IEEE; IEEE RAS Distinguished Lecturer, Co-Chair of IEEE RAS TC Digital Manufacturing and Human-Centered Automation and a member of the National Academy of Science and Engineering in Germany (acatech).

Tentative Title:
Evolvable field-level automation architectures to leverage AI for physical manufacturing and logistics systems

Abstract:
Manufacturing and logistic systems operate for decades and need to evolve to manufacture new products, increase quality, energy, or overall efficiency. Consequently, automation hardware and software adaptation in the operation phase is crucial. Means to design such automation architectures compliant to Industry 4.0 are of high economic interest. The talk will introduce means to analyze existing automation architectures as a first step to refactoring. In the second step, the integration of AI into such architectures will be discussed. Finally, automation architectures that ease the adaptation of physical manufacturing and logistics systems will be presented.

 

Dr. Michael Y. Wang

Biography:
Michael Y. Wang is the Professor and Head of Department of Mechanical and Aerospace Engineering at Monash University. He has numerous professional honors - National Science Foundation Research Initiation Award; Ralph R. Teetor Educational Award from Society of Automotive Engineers; LaRoux K. Gillespie Outstanding Young Manufacturing Engineer Award from Society of Manufacturing Engineers; Boeing-A.D. Welliver Faculty Summer Fellow, Boeing; Chang Jiang (Cheung Kong) Scholars Award from the Ministry of Education of China and Li Ka Shing Foundation (Hong Kong); Research Excellence Award of CUHK. He was the Editor-in-Chief of IEEE Trans. on Automation Science and Engineering. His main research interests are in robotic manipulation, learning and autonomous systems, manufacturing automation, and additive manufacturing. Before joining Monash University in 2022, he was the Founding Director of the Cheng Kar-Shun Robotics Institute, the Director of HKUST-BRIGHT DREAM ROBOTICS Joint Research Institute, and a Chair Professor of Mechanical and Aerospace Engineering as well as Electronic and Computer Engineering of Hong Kong University of Science and Technology (HKUST). Previously, he also served on the engineering faculty at University of Maryland, Chinese University of Hong Kong, and National University of Singapore. A recipient of ASME Design Automation Award, Professor Wang is a fellow of ASME and IEEE.

 

Dr. Luis Enrique Sucar

Biography:
Dr. L. Enrique Sucar is Senior Reseacrh Scientist at the National Institute for Astrpophysics, Optics and Electronics, Puebla, Mexico. He received a Master degree in Computer Systems from the Stanford University and a PhD in Computing from Imperial College. He has been an invited professor at Imperial College, UK; the University of British Columbia, Canada; INRIA, France and CREATE-NET, Italy. Dr. Sucar received the National Science Prize from the Mexican President in 2016. He is Member of the National Research System, the Mexican Science Academy, a Senior Member of the IEEE, and Ex-President of the Mexican Academy of Computing. He has more than 400 publications in journals and conference proceedings. He has served as president of the Mexican AI Society, has been member of the Advisory Board of IJCAI, and is associate editor of the journals Pattern Recognition and Computational Intelligence. He is interested in understanding and building intelligent systems that can interact with the real world, taking the best decisions under uncertainty, based on probabilistic and causal graphical models.

 

Important Dates

Special Session Proposal Submission Mar. 1
RA-L Submission Mar. 1
Regular and Special Session Paper Submission Mar. 1
↑ ↑ Final deadline without further extension ↑ ↑ Mar. 18
Workshop proposal, work in progress / industry paper / presentation only submission due
May 1
Paper Acceptance Notification May 25
Final Paper Submissions Due Jun. 25
Author Registration Due Jun. 25
Final Program Released Jul. 10
Case 2022 Conference! Aug. 20-24

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