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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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Francesco Marcelloni
University of Pisa
Italy
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Brief Bio
FRANCESCO MARCELLONI is full professor of Data Mining and Machine Learning at the University of Pisa. His main research interests include explainable artificial intelligence, federated learning, data mining for big data and streaming data, sentiment analysis and opinion mining, genetic fuzzy systems, and fuzzy clustering algorithms. He has co-edited three volumes, four journal special issues, and is (co-)author of a book and of more than 250 papers in international journals, books and conference proceedings. Recently, he has received the 2021 IEEE Transactions on Fuzzy Systems Outstanding Paper award and the 2022
IEEE Computational Intelligence Magazine Outstanding Paper award. He serves as associate editor of IEEE Transactions on Fuzzy Systems (IEEE), Information Sciences (Elsevier), Soft Computing (Springer), and is on the editorial board of a number of other international journals. He has coordinated various research projects funded by both public and private entities. He has also coordinated two Erasmus+ KA2 projects.
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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. From 1992 to 2000 he has been creator and head of DRN (Neural Networks Division) research group. From 2001 to 2004 he has been head of Intelligence in Instrumentation and Systems Laboratory (I2S / JE 2353) of UPEC. 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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Niki van Stein
Leiden University
Netherlands
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Brief Bio
Niki van Stein is a researcher in the Natural Computing Group of LIACS and manager of the applied data science lab. She received her PhD in Computer Science from Leiden University in 2018. Niki's research interests are in explainable AI for optimization and machine learning, global (Bayesian) optimization and neural architecture search.