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Joaquim Filipe
Polytechnic Institute of Setubal / INSTICC
Portugal
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Brief Bio
Joaquim B L Filipe is currently a Coordinator Professor of the School of Technology of the Polytechnic Institute of Setúbal (EST-Setúbal), Portugal. He got his PhD at the School of Computing of Staffordshire University, U.K, in 2000.
His main areas of research involve Artificial Intelligence and Multi-Agent System theory and applications to different domains, with an emphasis on social issues in activity coordination, especially in organizational modelling and simulation, where he has been actively involved in several R&D projects, including national and international programs. He represented EST-Setúbal in
several European projects.
He has over 200 publications, including papers in conferences and journals, edited books, and conference proceedings. He started several conference series, sponsored by INSTICC and technically co-sponsored or in cooperation with major International Associations.
He took part in over 100 conference and workshop program committees and he is on the editorial board of a Springer book series.
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Kurosh Madani
University of Paris-EST Créteil (UPEC)
France
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Brief Bio
Kurosh Madani is graduated in fundamental physics in June 1985 from PARIS 7 – Jussieu University. He received his MSc. in Microelectronics and chip architecture from University PARIS 11 (PARIS-SUD), Orsay, France, in September 1986. Received his Ph.D. in Electrical Engineering and Computer Sciences from University PARIS 11 (PARIS-SUD), Orsay, France, in February 1990. In 1995, he received the DHDR Doctor Hab. degree (senior research doctorate degree) from University PARIS 12 – Val de Marne. He works as Chair Professor in Electrical Engineering of Senart-FB Institute of Technology of University PARIS-EST Creteil (
UPEC), France. Co-creator of Images, Signals and Intelligent Systems Laboratory (LISSI / EA 3956) of UPEC in 2005, head of Intelligent Machines & Systems” research team of LISSI, he is also Vice-director of this laboratory. He has worked on both digital and analog implementation of massively parallel processors arrays for image processing, electro-optical random number generation, and both analog and digital Artificial Neural Networks (ANN) implementation. His current research interests include: - Complex structures and behaviors modeling, - self-organizing, modular and hybrid neural based information processing systems and their real-world and industrial applications, - humanoid and collective robotics - intelligent fault detection and diagnosis systems.
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Oleg Gusikhin
Ford Motor Company
United States
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Brief Bio
Dr. Oleg Gusikhin is a Senior Director, Data Science & Machine Learning at Ford Global Data Insight & Analytics, where he leads Supply Chain Analytics. He has over 30 years of experience in application of advanced technology and analytics in the automotive industry. During his tenure at Ford, he has created numerous high-impact long-lasting applications for Ford manufacturing, supply chain and connected vehicles, and holds over 100 patents. Dr. Gusikhin is a Fellow of IEEE, a Fellow of INFORMS and a Fellow of AAIA. He is a recipient of three Henry Ford Technology Awards in the Manufacturing, Research, and Product
Development categories, the 2025 INFORMS Innovative Applications in Analytics Award, and the 2014 INFORMS Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research. In addition, Dr. Gusikhin is a Lecturer at the University of Michigan Industrial & Operations Engineering and engineering faculty advisor at the Tauber Institute for Global Operations.
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Jurek Sasiadek
Carleton University
Canada
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Brief Bio
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