Confirmed Speakers for BICA 2025
Ricardo Gudwin
Prof. Ricardo Gudwin is actually an Associate Professor at the Faculty of Electrical and Computer Engineering, State University of Campinas - Brazil. He received the B.S. degree in Electrical Engineering in 1989, the M.S. degree in Electrical Engineering in 1992, and the Ph.D. in Electrical Engineering in 1996, all of them from the Faculty of Electrical and Computer Engineering, State University of Campinas - Brazil. His earlier research interests include fuzzy systems, neural networks, and evolutionary systems. His current research interests include the study of intelligence and intelligent systems, intelligent agents, semiotics, computational semiotics, and artificial cognition. Prof. Gudwin is the head of the "Computational Semiotics Group", and Scientific Member/Director of the Group for Research on Artificial Cognition within the DCA/FEEC/UNICAMP, a member of the board of governors of the SEE - Semiotics-Evolution-Energy Virtual Institute in Toronto, Canada, and a member of the editorial board of the "On Line Journal for Semiotics, Evolution, Energy Development" - ISSN 1492-3157, published by the SEE Virtual Institute. He was the editor-in-chief of the journal "Controle & Automação", published by the SBA - Brazilian Society for Automation from Sept. 2004 to Dec. 2008. He is actually a co-PI in the CEPID BRAINN (FAPESP Proc. 2013/07559-3), responsible for the research in the field of cognitive architectures.
Speech: On the Pursuit of Understanding and Consciousness in Cognitive Architectures
Human beings not only entertain a conversation with other beings, like an LLM does, but based on their sensory organs, are able to make sense of their surrounding environment, having feelings and experiences while interacting with it. They are able to truly understand the meaning of exchanged communications and evolve high-level thinking before acting in the world. In this talk, we investigate the role of Understanding, what it is, according to different thinkers, and how this capability might be made available in a cognitive architecture. We discuss whether LLMs (and Transformers, in a general sense) can be afforded to exhibit true understanding, or if they just simulate this capability, acting like “probabilistic parrots”, without a true understanding of what they say. Finally, we propose an ontology of reality to support the development of Cognitive Architectures, which we believe might enable future artificial agents to attain a human-comparable understanding of reality, and possibly consciousness.
Ron Sun
Ron Sun is a cognitive scientist who made significant contributions to computational psychology and other areas of cognitive science and artificial intelligence. He is currently Professor of Cognitive Science at Rensselaer Polytechnic Institute, and was formerly James C. Dowell Professor of Engineering and Professor of Computer Science at the University of Missouri. He received his Ph.D. in 1992 from Brandeis University.
Speech: Rethinking Rationality and Intelligence in AI Through a Cognitive Architecture
This talk examines the literature on rationality and intelligence in AI systems, and delves into a specific approach — the development of a neural-symbolic cognitive architecture. The discussion covers various forms of rationality, different ideas about intelligence, nature of human activities, roles of motivation, and so on, all examined through the lens of the cognitive architecture. This talk argues that recent computational models are more sophisticated than often assumed: They are well-equipped to overcome many of the criticisms leveled against AI.
Sean Kugele
Dr. Kugele's research focuses on artificial intelligence, cognitive modeling, and neuro-symbolic systems. The goal of his research is to understand how natural minds (such as human minds) work and to implement biologically inspired software systems based on the same principles. Dr. Kugele has worked for over a decade as a software engineer and software architect. He has undergraduate degrees in computer science, mathematics, and anthropology, and a PhD in computer science from the University of Memphis.
Vassilis G. Kaburlasos
Vassilis G. Kaburlasos has received the Diploma degree from the National Technical University of Athens, Greece, in 1986, and the M.Sc. and Ph.D. degrees from the University of Nevada, Reno, NV, USA, in 1989 and 1992, respectively, all in electrical engineering. He currently serves as a Tenured Full Professor in the Department of Informatics, Computer and Telecommunication Engineering (at Serres) of the International Hellenic University (IHU), Greece. During 2019-2024 he served as an elected member of IHU’s Research Committee. He has been the founder and director during 2016-2023 of the HUman-MAchines INteraction (HUMAIN) research Lab at the Department of Computer Science of IHU in Kavala having accessed projects of total budget over 5M EUR. He has been participant or (principal) investigator in 32 research projects, funded either publicly or privately, in the USA and in the European Union. He has been a member of the technical/advisory committee or an invited speaker in numerous international conferences and a reviewer of more than 60 indexed (WoS) journals. He has (co)authored more than 230 scientific research articles in indexed journals, refereed conferences, edited volumes and books. He is the co-owner of 2 patents in Greece and another 3 in Europe. His research interests include modeling of cyber-physical systems, including intelligent robots, with breakthrough contributions in the “Lattice Computing (LC) information processing paradigm” toward computing with semantics. Dr. Kaburlasos is a member of several professional, scientific, and honor societies around the world including the Sigma Xi, Phi Kappa Phi, Tau Beta Pi, Eta Kappa Nu, and the Technical Chamber of Greece. Since 2019, his name is included in the top 2% of “career long” researchers worldwide in the field “Artificial Intelligence & Image Processing” according to Mendeley Data, http://doi.org/10.17632/btchxktzyw.2 /3 /4 /6 /7 . Since February 2024, he is a member of the IEEE P3430 Working Group on “A Holistic Framework for AI Foundation Models”.