Professor Hamid R. Arabnia received a Ph.D. degree in Computer Science from the University of Kent (England) in 1987. He is currently a Professor Emeritus of Computer Science at University of Georgia, USA, where he has been since October 1987. His research interests include parallel and distributed processing techniques & algorithms, supercomputing, Data Science, imaging science, and other compute intensive problems. Applications of interest include: medical imaging and security. Most recent activities include: Studying ways to promote legislation that would prevent cyber-stalking, cyber-harassment, and cyber-bullying. As a victim of cyber-harassment and cyber-bullying, in 2017 he won a lawsuit with damages awarded to him for a total of $2.3 Million and $656K attorney costs. Since this court case was one of the few cases of its kind in the United States, this ruling is considered to be important; Final Judgement for damages was issued in Leon County Courthouse of Tallahassee in Florida by Circuit Court Judge. Prof. Arabnia is Editor-in-Chief of The Journal of Supercomputing (Springer). He is also on the editorial and advisory boards of 30 other journals. He is the book series editor-in-chief of "Transactions of Computational Science and Computational Intelligence" (Springer). He has won 12 distinguished awards, including the "Outstanding Research Contributions to the Field of Supercomputing" (President of IEEE/SMC) and "Distinguished Research Award" for Outstanding Contributions to Adaptable Communication Systems (ACM SIGAPP IMCOM). Dr. Arabnia is Fellow and Advisor of Center of Excellence in Terrorism, Resilience, Intelligence & Organized Crime Research (CENTRIC). He has been a PI/Co-PI on about $8 Million externally funded projects, about $200K internally funded projects, and about $4 Million equipment grants. During his tenure as Director of Graduate Programs, Dr. Arabnia secured the largest level of funding in the history of the department for supporting the research and education of graduate students (PhD, MS). Dr. Arabnia has delivered a number of keynote and plenary lectures at international conferences; most recently at: The 14th IEEE International Conference on Parallel and Distributed Systems (ICPADS, Australia); International Conference on Future Generation Communication and Networking (FGCN / IEEE CS, Sanya); The 10th IEEE International Conference on High Performance Computing and Communications (HPCC, Dalian); and ACM IMCOM International Conference. He has also delivered a number of "distinguished lectures" at various universities and research units/centers (USA, Spain, South Korea, Japan, Iran, Saudi Arabia, UK, Canada, Turkey, China, Ireland, Australia, ...); his distinguished lectures were funded and sponsored by US Department of Defense, SERSC of Republic of Korea, US National Science Foundation, H2020 of Europe, and others.

 

Ken Ferens is an Assistant Professor at the Department of Electrical and Computer Engineering (ECE), University of Manitoba, Canada. He is the Computer Engineering Champion in the Centre for Engineering Professional Practice and Engineering Education. He is the director of the Applied Cognitive Intelligence (ACI) Research Group in the Department of ECE. He obtained his Ph.D. in 1996 from the University of Manitoba, and is a member of The Association of Professional Engineers and Geoscientists of the Province of Manitoba. He has authored over 100 publications in his research areas. Dr. Ferens is a senior member of the Institute of Electrical & Electronics Engineers (IEEE); a member of the Canadian Engineering Education Association; the Chair of the EduManCom Chapter of the IEEE; the Vice-Chair of the Computer and Computational Intelligence Chapter of the IEEE; and the Chair of the Industry, Teaching Assistants, and Student Forums, for Engineering Curriculum Review and Improvement.

 

David de la Fuente is a Full Professor of Oviedo University, from 2010. He has published 144 papers (h-index of 22). His area of research includes: Artificial Intelligence, Forecasting, Simulation, and Fuzzy set theory. He has organized a number of international workshops and sessions. Dr. Fuente's research results in the area of decision support systems have been show-cased in a number of publications. He is also known for his research contributions in the area of operational research. He has presented invited talks in the area of Artificial Intelligence and applications in industry. He has refereed for numerous journals and book publishers. He is an active member of the AI research community.

 

Elena B. Kozerenko is the Head of Computational Linguistics and Cognitive Text Processing Research Group and Leading Researcher of the Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, Institute of Informatics Problems (1984-Present); Ph.D. -  Theoretical Foundations of Informatics (Computational Linguistics) - 1995; Specialist (equal to MA Degree) - Applied and Structural Linguistics, English  and Italian Languages, 1981, Diploma with Excellence, Minsk State Linguistic University, Belarus (Former Soviet Union). Synergistic Activities include: Author of Cognitive Transfer Grammar formalism, i.e. the syntactic-semantic processor based on the system of rules presented in the constraint-based formalism called the Cognitive Transfer Grammar for the English-Russian machine translation system Cognitive Translator. Chair of the International Workshop "Intelligent Linguistic Technologies" of the ICAI 2003 - 2019, and Lingware 2019 Session - CSCI'19. Dr. Kozerenko has 63 research publications in scientific journals and research proceedings. Teaching and academic activities include: Moscow Pedagogical State University, Institute "Higher School of Education" Job Title: Chair for Computational Linguistics and Formal Language Models (part time job); Job Description: Administration of the Educational Programs in Theoretical, General, Typological Linguistics, Educational Program Director in Computational Linguistics and Formal Language Models, Professor in Gereral and Computational Linguistics, Linguistic Semantics, Syntax, Language Corpora.

 

Professor Jose Angel Olivas Varela received his M.S. degree in Philosophy in 1990 (USC, Spain), Master on Knowledge Engineering of the Department of Artificial Intelligence, UPM in 1992, and his Ph.D. in Computer Science in 2000 (UCLM, Spain). In 2001, he was Postdoc Visiting Scholar at Lotfi A. Zadeh's (father of Fuzzy Logic) BISC (Berkeley Initiative in Soft Computing), University of California-Berkeley, USA. He is affiliated with BISC and with the Artificial Intelligence Center of the SRI International of the Stanford University (Prof. Richard Waldinger). His current main research interests are in the field of Soft Computing for Information Retrieval, Data Analysis and Artificial Intelligence and Knowledge Engineering applications. He received the Environment Research Award 2002 from the Madrid Council (Spain) for his PhD. Thesis. Author of more than 250 scientific contributions. He has provided his expertise to corporations and also has chaired a number of technical and research workshops in his areas of expertise. He has edited a number of books and guest edited for various journals.

 

Fernando G. Tinetti has a PhD in Computer Science and is a Professor at Facultad de Informatica, Universidad Nacional de La Plata, La Plata, Argentina. He is also a researcher of the Comision Investigaciones Cientificas de la Provincia de Buenos Aires, Argentina. He is a recipient of the NSF-TCPP Early Adopter Award, NSF/IEEE-TCPP, Curriculum Initiative on Parallel and Distributed Computing. He is the author/co-author of more than one hundred papers in International Journals and Computer Science Conferences. His areas of interest and experience include: High Performance Computing, Parallel and Distributed Computing, Cloud and Edge Computing, Real-Time Systems and Applications, Big Data Processing, Data Center and Infrastructure Performance Evaluation, Robotic Systems and Applications. He has co-edited a number of books in HPC.

Introduction.- PART I: ICAI'20.- Brain models, Brain mapping, Cognitive science.- Natural language processing.- Fuzzy logic and soft computing.- Social impact of AI.- Emerging technologies.- Statistical learning theory.- Unsupervised and Supervised Learning.- Multivariate analysis.- Hierarchical learning models.- Relational learning models.- Bayesian methods.- Meta learning.- Stochastic optimization.- Heuristic optimization techniques.- Neural networks and variations.- Reinforcement learning.- PART II: ACC 2020.- Novel Computationally Intelligent algorithms.- Bio Inspired Cognitive Algorithms.- Improving Cognition in machine learning systems.- Modeling Human Brain processing systems.- Multimodal learning systems.- Autonomous learning systems.- Reinforced learning.- Conclusion.