Machine learning (ML) is changing the world, and in particular, the world of automation. So far, this wave of ML research has also influenced the main themes at IEEE CASE 2018-2021: Knowledge-based Automation, Smart Automation, Automation Analytics, and Data-Driven Automation. The critical question, however, is: How much of groundbreaking ML research has been performed in our community in recent years? Are we leading actors, or more followers, applying what others have already formulated? An AdHoc on Machine Learning for Automation has recently been initiated by the CASE steering committee. The goal is that CASE, T-ASE, and relevant TCs shall become important players in the tough scientific race around ML that is going on right now. This panel discussion will take that goal as a starting point, and then reason about how we can build strong automation related ML research, by identifying organizational and infrastructural support, but also niche areas where our research community should take the lead. The goal is simply to achieve results that counts, both concerning fundamental methodology development and applications in strategic areas, which cause not small but big improvements within the limited resources we still have on our common planet.
Bengt Lennartson, Professor, Division of Systems and Control, Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Biography: Bengt Lennartson is a Professor of the Chair of Automation since 1999 at Chalmers University of Technology, Gothenburg, Sweden. He has been Associate Editor for Automatica and IEEE Transaction on Automation Science and Engineering, General Chair of IEEE CASE 2015, WODES 2008 and Dean of Education at Chalmers. He is the (co)author of 300+ peer reviewed international papers, and his research is currently focused on AI planning and learning, as well as sustainable production. He is IEEE Fellow.
Maria Pia Fanti, Professor, Department of Electric and Information Engineering, Polytechnic University of Bari, Italy.
Biography: Maria Pia Fanti has been with the Department of Electrical and Information Engineering of the Polytechnic of Bari, Italy, since 1983 and she is currently a full professor of system and control engineering. Her research interests include management and modeling of complex systems, such as transportation, logistics and manufacturing systems. Prof. Fanti has published more than 315 papers and two textbooks on her research topics. She was senior editor of the IEEE TASE and she is AE of the IEEE Trans. on SMC: Systems. She was member at large of the Board of Governors of the IEEE SMCS, and currently she is member of the AdCom of the IEEE RAS, and chair of the RAS. Prof. Fanti was General Chair of the 2011 IEEE CASE and the 2019 IEEE SMC.
Weihong "Grace" Guo, Associate Professor, Department of Industrial and Systems Engineering, Rutgers, The State University of New Jersey.
Biography: Weihong "Grace" Guo is an Associate Professor in the Department of Industrial and Systems Engineering at Rutgers University-New Brunswick, USA. She earned her B.S. degree in Industrial Engineering from Tsinghua University, China, in 2010 and her Ph.D. in Industrial & Operations Engineering from the University of Michigan, Ann Arbor, in 2015. Her research focuses on manufacturing data analytics, process monitoring, anomaly detection, quality evaluation, and system informatics. She is a member of IEEE, IISE, INFORMS, ASME, and Tau Beta Pi.
Qing-Shan Jia, Professor, Center for Intelligent and Networked Systems, Tsinghua University, Beijing, China.
Biography: Qing-Shan Jia is a full professor at Center for Intelligent and Networked Systems, Department of Automation, Tsinghua University, Beijing, China. His research interest is to develop an integrated datadriven, statistical, and computational approach to find designs and decision-making policies which have simple structures and guaranteed good performance. His work relies on strong collaborations with experts in manufacturing systems, energy systems, autonomous systems, and smart cities. He was an AE of IEEE T-ASE and T-AC, and is a member of the IEEE CASE Steering Committee.
Feng Ju, Associate Professor, School of Computing and Augmented Intelligence, Arizona State University, Phoenix, USA.
Biography: Dr. Feng Ju is an Associate Professor with the School of Computing and Augmented Intelligence, Arizona State University. His research interests include machine learning and optimization of smart manufacturing systems and additive manufacturing. He was a recipient of multiple awards, including Dr. Hamed K. Eldin Outstanding Early Career IE in Academia Award, the Best Paper Awards in IISE Transactions and IFAC MIM, and the Best Student Paper Award in IEEE CASE.
Peter B. Luh, Professor, Department of Electrical Engineering, National Taiwan University Electrical and Computer Engineering, University of Connecticut, Storrs, Connecticut, USA.
Biography: Peter Luh was with U. Connecticut 1980-2020, and was a Board of Trustees Distinguished Professor and the SNET Professor of Communications & Information Technologies upon retirement. He is now a Distinguished Chair Professor at National Taiwan University. He was the founding EiC of T-ASE, a CoFounder of CASE, and is a member of the IEEE Publication Services and Products Board, and the Chair of its Publishing Conduct Committee. His research includes intelligent manufacturing, smart grid, and energysmart buildings, with optimization cutting across them. He received RAS 2013 Pioneer Award, 2017 George Saridis Leadership Award, and T-ASE 2019 Best Paper Award.
Frank C. Park, Professor of Mechanical Engineering, Seoul National University, Seoul, South Korea.
Frank C. Park is Professor of Mechanical Engineering and also Vice-Dean of the Graduate School of Data Science at Seoul National University. He received the B.S. in EECS from MIT in 1985, the Ph.D. in applied mathematics from Harvard in 1991, and was on the faculty of the University of California, Irvine from 1991 to 1994 before joining SNU in 1995. He is a fellow of the IEEE, and has held adjunct faculty positions with the HKUST Robotics Institute in Hong Kong, the Interactive Computing Department at Georgia Tech, and the NYU Courant Institute. His research interests include robotics, computer vision, mathematical data science, and related areas of applied mathematics. He is a former Editor-in-Chief for the IEEE Transactions on Robotics, developer of the EDX course Robot Mechanics and Control I-II, and author (with Kevin Lynch) of the textbook Modern Robotics: Mechanics, Planning, and Control (Cambridge University Press, 2017). He is president of the IEEE Robotics and Automation Society (2022–2023), and founder and CEO of the industrial AI startup Saige Research (http://saige.ai).
Karinne Ramirez-Amaro, Associate Professor, Division of Systems and Control, Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Biography: Dr. Karinne Ramirez-Amaro is an Associate professor at Chalmers University of Technology since March 2022. Previously, she was a post-doctoral researcher at the Technical University of Munich (TUM), Germany. She completed her Ph.D. (summa cum laude) at the Department of Electrical and Computer Engineering at TUM in 2015. She has received different awards, e.g. the price of excellent Doctoral degree for female engineering students and the Google Anita Borg scholarship. In 2022, Karinne was elected as member of the Administrative Committee (AdCom) from the IEEE Robotics and Automation Society (RAS) and she is the chair of the IEEE RAS Women in Engineering (WiE). Her research interests include Explainable AI, Semantic Representations, Cause-based Learning Methods, Collaborative Robotics, and Human Activity Recognition and Understanding.
MengChu Zhou, Professor, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, USA.
Biography: MengChu Zhou is Distinguished Professor at New Jersey Institute of Technology. His interests are in automation, Internet of Things, and AI. He has 1000+ publications including over 600 IEEE transactions papers, 12 books, and 30 patents and 29 book-chapters. He is Fellow of IEEE, IFAC, AAAS, CAA and NAI.
Panel II: Artificial Intelligence in the Mexican Industry
Artificial Intelligence (AI) uses computer algorithms to simulate human intelligence, mainly focused on learning and decision-making processes. Due to the maturity of the area and the new advances in AI branches such as machine and deep learning, the industrial applications of AI have been increasing rapidly. Today AI is present in the algorithms to drive cars, land planes, render images, make decisions, among many other applications. This growth makes us wonder, what is the future of AI in autonomous vehicles (cars, planes)? How will AI solve problems in artificial vision or in autonomous surgical systems? Regulations and ethical questions must be addressed when using AI to solve critical problems. This panel looks at how Continental, Intel and Wizeline view the use of AI to solve industrial problems.
Antonio Ramírez Treviño
Dr. Andres Mendez Vázquez, Dr. Mendez is currently with Cinvestav Guadalajara, his research interest fields are the artificial intelligence, mainly the areas of machine and deep learning. He has participated in many projects of Machine Learning, Artificial Intelligence and Deep Learning for several startup, USA Army, Mexican Air Force, Oracle MDC, IBM Mexico, etc.
Dr. Alberto de Obeso, Dr. de Obeso is with Wizeline as the Director of Artificial Intelligence. His ultimate goal as a professional is to deliver solutions with clear advantages over classic approaches by combining sound software design principles with powerful techniques derived from the Artificial Intelligence realm. He has 18+ years of experience developing software and data-driven solutions in different languages and platforms for complex organizations. 7+ years of performing increasingly demanding leadership roles, his intent is to keep growing on this path. During his doctoral studies in the UK, he explored complex problem-solving behavior from a computational perspective. He is a postgraduate teacher at ITESO and TEC de Monterrey. and has two patent applications.
Dr. Julio Zamora, Dr. Zamora is Principal Engineer and Senior Research Scientist Manager at Intel Labs, Leading globally the Human Robot Collaboration Group as a part of Intelligent System Research Group. He received a Masters degree in Computer Sciences and PhD in Electric Engineering from CINVESTAV. Dr. Zamora had a post-Doctoral position at KAIST, Korea. He was nominated for the W.K. Clifford international price for his contributions to geometric algebra, introducing the Quadric Geometric Algebra and the formulation of Robot dynamics in terms of octonions. He is member of the National Research System, the Mexican Association for Computer Vision, Neural Computing and Robotics, and Senior member of IEEE. He has more than 60 patents in process and more than 30 publications in journals, book chapters and conference proceedings. His research interests include Artificial Intelligence, Computer Vision, Geometric Algebras, Robotics, and Image Processing.
MBA Edú Brasil López San Vicente, He is currently the Director of Research and Development of Continental Automotive Guadalajara. He is responsible for the innovation and business strategy of “Vehicle Networking and Information” in Mexico, as well as the administration and direction of the engineering community of all its business units and core areas of the sector “Automotive Technologies” of Continental Automotive in Mexico. He has more than 20 years of experience in development and innovation of electronic products for the automotive and telecommunications industries, working in Mexico, Japan, USA and Germany. He has led worldwide teams for the innovation, research and development of mechanical products, and he has designed strategies to establish engineering centers in Mexico and led the transfer of responsibilities from Japan and the United States to Mexico.
Panel III: Trends in Industrial Automation
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