IJCCI Conference Co-Chairs
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Juan Julian Merelo
ICAR/CITIC, University of Granada
Spain
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Brief Bio
Juan Julian Merelo is professor at the University of Granada, where he has been working since 1988. His main interests are evolutionary algorithms, distributed/parallel computing and computational intelligence in games.
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Kevin Warwick (honorary)
School of Systems Engineering, University of Reading and Coventry University
United Kingdom
http://www.kevinwarwick.com/
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Brief Bio
Kevin Warwick is Professor of Cybernetics at the University of Reading, England, where he carries out research in artificial intelligence, control, robotics and biomedical engineering. He took his first degree at Aston University, followed by a PhD and research post at Imperial College London. He subsequently held positions at Oxford, Newcastle and Warwick Universities before being offered the Chair at Reading. He is a Chartered Engineer (CEng.) and is a Fellow of The Institution of Engineering & Technology (FIET). Kevin Warwick is the youngest person ever to become a Fellow of the City & Guilds of London Institu
te (FCGI). He is the author or co-author of more than 500 research papers and has written or edited 27 books (three for general readership), as well as numerous magazine and newspaper articles on scientific and general subjects.
Kevin has been awarded higher doctorates (DSc) both by Imperial College and the Czech Academy of Sciences, Prague and has received Honorary Doctorates from 6 Universities. He has appeared in the Guiness Book of Records for his research on several occasions and is perhaps best known for his implant self-experimentation, linking his own nervous system with a computer network.
The Institute of Physics selected Kevin as one of only 7 eminent scientists to illustrate the ethical impact their scientific work can have: the others being Galileo, Einstein, Curie, Nobel, Oppenheimer and Rotblat.
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Christian Wagner
University of Nottingham
United Kingdom
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Brief Bio
Christian Wagner received his Ph.D. in Computer Science in 2009 from the University of Essex, UK. He is currently a Professor of Computer Science at the University of Nottingham, and founding director of the Lab for Uncertainty in Data and Decision Making (LUCID). His research focusses on the capture, modelling & handling of uncertain data arising from heterogeneous data sources, with a particular emphasis on designing interpretable AI based decision support systems. In 2017, he was recognised as a RISE (Recognising Inspirational Scientists and Engineers) Connector by EPSRC. His work ranges from decision support
in cyber security and environmental management to personalisation and control in manufacturing. He has led a series of research projects with partners from industry and government with an overall value of around £10m and co/developed multiple open source software frameworks, making cutting edge research accessible to research communities beyond computer science.
Dr Wagner is an Associate Editor of the IEEE Transactions on Fuzzy Systems journal, Chair of the IEEE CIS Technical Committee on Fuzzy Systems and Task Force on Cyber Security; elected member-at-large of the IEEE Computational Intelligence Society (CIS) Administrative Committee for 2018-2020. He is a General Co-Chair of Fuzz-IEEE 2021 in Luxembourg, Europe.
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Jonathan Garibaldi
School of Computer Science, University of Nottingham
United Kingdom
http://www.cs.nott.ac.uk/~jmg/home.shtml
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Brief Bio
Prof Jon Garibaldi's main research interest is in the modelling of human decision making, primarily in the context of medical applications. His work to date has concentrated on utilising fuzzy logic to model the imprecision and uncertainty inherent in medical knowledge representation and decision making. This has been applied in areas such as classification of breast cancer, identification of Alzheimer's disease, and the assessment of immediate neonatal outcome. A particular interest is in the transfer of medical intelligent systems into clinical use and this has led to the study of methods of evaluating intellig
ent systems and mechanisms for their implementation. Prof Garibaldi also has an interest in generic machine learning, such as clustering, classification and optimisation, particularly when applied to the optimisation of decision making models, and in the study of adaptive and time-varying behaviour.
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