Plenaries, Keynotes and Invited Guest Talks
Prof. Maja Matarić
A Robot Just for You
– Personalized Human-Robot Interaction and the Future of Work and Care –
Time: Oct 2, 9 am-9:45 am, Main Hall
As robots become part of our world, we demand that they understand us, predict our needs and wants, and adapt to us as we change our moods and minds, learn, grow, and age. The nexus created by major improvements in machine learning for machine perception, navigation, and natural language processing has enabled human-robot interaction in real-world contexts, just as the need for human services continues to grow, from elder care to nursing to education and training, positively impacting user health and quality of life. This talk will discuss work that brings robotics together with machine learning for user modeling, signal processing, and affective computing in order to enable robots to understand, interact, and adapt to users’ ever-changing needs. The talk will cover methods and challenges of using multi-modal interaction data and expressive robot behavior to monitor, coach, motivate, and support a wide variety of user populations and use cases. We will cover insights from work with users across the age span (children, adults, elderly), ability span (typically developing, autism, stroke, Alzheimer’s), contexts (schools, therapy centers, homes), and deployment durations (up to 6 months), as well as commercial implications.
Prof. Maja Matarić is Chan Soon-Shiong Distinguished Professor of Computer Science, Neuroscience, and Pediatrics at the University of Southern California (USC), founding director of the USC Robotics and Autonomous Systems Center, and Interim Vice President of Research. She received a PhD and MS in Computer Science and Artificial Intelligence MIT, and BS in Computer Science from the University of Kansas. She is a Fellow of the AAAS, IEEE, AAAI, and ACM, recipient of the Presidential Award for Excellence in Science, Mathematics & Engineering Mentoring, the Anita Borg Institute Women of Vision Award for Innovation, the Okawa Foundation Award, NSF Career Award, MIT TR35 Innovation Award, the IEEE Robotics and Automation Society Early Career Award, and the USC Remarkable Woman Award, among others. Prof. Mataric´ is the author of the popular textbook “The Robotics Primer” and has published extensively (h-index 100; 39,594 citations as of 1/30/21). She has served on a number of advisory boards, including the National Science Foundation CISE Division, the Computing Community Consortium (CCC) Council, Willow Garage, and Evolution Robotics.
Prof. Matarić has made a series of pioneering contributions to the field of robotics. Her early work was in robot navigation and mapping; she then made contributions to multi-robot coordination and swarm control. Next, she did some of the earliest work in robot learning from demonstration. She is now best known for founding the field of socially assistive robotics, where her research is developing human-robot interaction algorithms and methods for supporting behavior change in convalescence, rehabilitation, training, and education. Her research has developed robot-assisted therapies for children with autism spectrum disorders, stroke and traumatic brain injury survivors, and individuals with Alzheimer’s disease and other forms of dementia, and has deployed robots in complex environments including homes, nursing homes, hospitals, and classrooms for weeks and months at a time, collecting unprecedented datasets that enabled novel models and personalization strategies . She is also co-founder of Embodied, Inc. where she served as chief science officer in 2016-2018; in May 2020 Embodied launched Moxie, an in-home socially assistive robot for children.
Prof. Matarić is recognized nationally for the scale and impact of her mentoring and K-12 STEM outreach activities. She received the Presidential Awards for Excellence in Science, Mathematics & Engineering Mentoring in 2011 from President Obama, and the USC Mellon Mentoring Award and Provost’s Mentoring Award. She is the lead of the USC Viterbi School of Engineering K-12 STEM Center, and has raised federal, corporate, and foundation support for and developed free open-source curricular materials for elementary, middle school, and high school robotics courses, K-12 teacher development programs, K-12 STEM equity and inclusion programs, and after-school robotics programs, and competitions training, all aiming to engage student interests in science, technology, engineering, and math (STEM) topics.
Prof. Matarić’s university leadership experience includes serving as the USC Interim Vice President of Research (2020-2021), USC Viterbi School of Engineering Vice Dean of Research (2006-2019), and the elected President of the USC faculty and the Academic Senate (2006-2007).
Susumu Tachi, Ph.D.
Telexistence and Society
– Toward the Extension of Human Existence and Capabilities
Oct. 2, 3:00pm-3:45pm, Main Hall
Although telework is feasible for so-called white-collar jobs, many jobs that support society at its core, such as medical care, welfare, water supply, electricity, convenience stores, supermarkets, construction, and civil engineering, require employees to be physically present, making remote working difficult. This is a problem that can be solved if we can use telexistence technology to make physical robots work as our alter egos. Telexistence is a concept that denotes an extension of human existence, wherein a person exists wholly in a location other than their actual current location and can perform tasks freely there. The location that differs from the location where the person physically exists can be a real space or a computer-generated virtual space. The latter case, i.e., telexistence in a virtual space, is usually called virtual reality. Furthermore, by matching the real space with the virtual space, it is possible to telexist in the real space through the virtual space or to act by adding information from the virtual space to the real space.
By distributing avatar robots around the world, users can freely use their avatar robot bodies as substitutes to release their time and space restrictions and enable their unknown experiences. As a result, a “telexistence society” can be realized, in which people’s capabilities can be used freely. It will be possible to respond instantly from a safe place during disasters and emergencies, and this technology can also be used routinely to dispatch medical services, caregivers, physicians, and experts to remote areas. Thanks to the creation of the Virtual Human Teleportation Industry, convenience and motivation in the lives of citizens will greatly improve, and it is anticipated that a healthy and pleasant lifestyle will be realized in a clean and energy-conserving society.
This keynote offers a historical perspective on the present situation and provides an overview of the forthcoming telexistence society from a bird’s-eye view.
Professor Susumu Tachi received his Ph.D. in mathematical engineering and information physics from the University of Tokyo in 1973, after which he joined the Faculty of Engineering of the University of Tokyo. In 1975 he moved to the Mechanical Engineering Laboratory, Ministry of International Trade and Industry, where he served as the Director of the Remote-Control Division and the Biorobotics Division. In 1989, he rejoined the University of Tokyo, and served as a Professor at the Department of Information Physics and Computing till 2009 when he was conferred Professor Emeritus. Between 2009 and 2015 he was Professor of Graduate School of Media Design and the Director of the International Virtual Reality Center at Keio University. In 2017, he founded and became Chairman of Telexistence, Inc.
Currently, he continues his research and activities for the dissemination and social implementation of virtual reality and telexistence at the University of Tokyo’s Research Center for Advanced Science and Technology, and the Institute of Gerontology of the University of Tokyo.
One of his early scientific achievements is the invention (1975) and development of an intelligent mobile robot system for the blind called Guide Dog Robot (1976-1983), which is the first of its kind. This system is known as MELDOG. In 1980, Dr. Tachi invented the concept of telexistence, which enables a highly realistic sense of existence in a remote place without any actual travel, and has been working on the realization of telexistence since then.
Prof. Tachi is a founding director and a fellow of the Robotics Society of Japan (RSJ), the 46th President and a fellow of the Society of Instrument and Control Engineers (SICE), a fellow of the Japan Society of Mechanical Engineers (JSME), and is the founding President of the Virtual Reality Society of Japan (VRSJ). He initiated and founded ICAT (International Conference on Artificial Reality and Telexistence) in 1991 and IVRC (International-collegiate Virtual Reality Contest) in 1993. He was a member of IEEE VR Steering Committee from 1998 to 2017.
Dr. Tachi has received a number of awards, a few of which are listed here: TIME Magazine Coolest Invention (2003), Laval Mayenne Awards (2003, 2005), Good Design Award (2006), ASIAGRAPH Takumi Award (2007), VRSJ Distinguished Contribution Award (2006), RSJ Founding Contribution Award (2012), Japan Minister of International Trade and Industry Prize (1988), Japan Minister of Education, Culture, Sports, Science and Technology Prize (2011), Governor of Tokyo Prize (2011), IMEKO Distinguished Service Award (1997), and IEEE Virtual Realty Career Award (2007). Dr. Tachi was inducted into the inaugural class of the IEEE Virtual Reality Academy in 2022, and he is the the first recipient of the Research Achievement Award established in 2022 by the Virtual Reality Society of Japan. For more achievements and recognition please see: https://tachilab.org/en/members/susumu_tachi.html
Prof. Francisco Herrera
Trustworthy Artificial Intelligence- Key Elements and Challenges
Tue Oct 3rd. 9:00 am – 9:45am, Main Hall
Francisco Herrera Triguero, is professor and director of the research group ‘Soft Computing and Intelligent Information Systems’ at the University of Granada. He is director of the Andalusian Interuniversity Institute in Data Science and Computational Intelligence (DaSCI) at the University of Granada and the University of Jaén.
He studied Mathematics and continued his doctorate in Artificial Intelligence (1991) in the department of Computer Science and Artificial Intelligence, where he obtained the chair in 2005. He is currently considered one of the most influential Spanish scientists in the world in the field of Computer Science and Engineering.
He has been the supervisor of 43 Ph.D. students. He has published more than 400 journal papers that have received more than 62000 citations (Scholar Google, H-index 12i). He is coauthor of the books “Genetic Fuzzy Systems” (World Scientific, 2001) and “Data Preprocessing in Data Mining” (Springer, 2015), “The 2-tuple Linguistic Model. Computing with Words in Decision Making” (Springer, 2015), “Multilabel Classification. Problem analysis, metrics and techniques” (Springer, 2016), “Multiple Instance Learning. Foundations and Algorithms” (Springer, 2016) and “Learning from Imbalanced DataSets” (Springer, 2018).
He currently acts as Editor in Chief of the international journals “Information Fusion” (Elsevier) and “Progress in Artificial Intelligence” (Springer). He acts as editorial member of a dozen of journals.
He received the following honors and awards: ECCAI Fellow 2009, IFSA Fellow 2013, 2010 Spanish National Award on Computer Science ARITMEL to the “Spanish Engineer on Computer Science”, International Cajastur “Mamdani” Prize for Soft Computing (Fourth Edition, 2010), IEEE Transactions on Fuzzy System Outstanding 2008 and 2012 Paper Award (bestowed in 2011 and 2015 respectively), 2011 Lotfi A. Zadeh Prize Best paper Award of the International Fuzzy Systems Association, 2013 AEPIA Award to a scientific career in Artificial Intelligence, and 2014 XV Andalucía Research Prize Maimónides (by the regional government of Andalucía), 2017 Security Forum I+D+I Prize, and 2017 Andalucía Medal (by the regional government of Andalucía), 2018 “Granada: Science and Innovation City”.
He has been selected as a Highly Cited Researcher (in the fields of Computer Science and Engineering, respectively, 2014 to present, Clarivate Analytics).
His current research interests include among others, soft computing (including fuzzy modeling, evolutionary algorithms and deep learning), computing with words, information fusion and decision making, and data science (including data preprocessing, prediction and big data).
Can Digital Intelligence and Cyber Physical Social Systems Achieve Global Food Security and Sustainability?
In ecosystems, carbon and water are the sources of life and the core elements for ecological structures and functions. Essentially, plants fix carbon through photosynthesis and provide primary productivity for ecosystems, but through transpiration they also consume water resources that could be used for human production and life, thus maintain the natural balance between carbon and water. In modern societies, key elements, main processes, and critical mechanisms for regulating and controlling ecological systems are intrinsically entangled and related studies have emerged as major challenges and the new frontier of ecological management research and complexity sciences.
Digital Intelligence and Cyber Physical Social Systems (CPSS) are becoming the new research paradigm that has significantly shifted normal and conventional thinking and practices in many scientific fields, including ecological science and sustainability studies. This report outlines our recent effort in using big data, AI, digital twins, metaverses, and parallel intelligence to modeling, analysis, and managing the complex relationship and balance among on plants, carbons, waters in arid and semi-arid ecosystems where water resources are scarce. It introduces the carbon-water balance and its potential mechanisms at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Specific results on Yellow River Region and general impact of the carbon-water balance at different ecosystem management decision-making processes will be reported. Finally, we will address issues and directions of applying intelligent science and technology for complexity management of regional ecosystems in the context of global change and the Anthropocene.
Yanfen Wang is a Professor in ecology at the University of Chinese Academy of Sciences (UCAS). She received her Ph.D. degree in ecology from the Institute of Botany, Chinese Academy of Sciences, Beijing, China, in 2001. Prof. Wang has served as the Vice President and Executive Vice President of UCAS since 2008 and 2018, respectively. She has also been the Vice Chairman of the China Ecological Society since 2018 and China Natural Resources Society since 2019, as well as an independent board member of the International Center for Integrated Mountain Development (ICIMOD) since 2014.
Prof. Wang’s current research focus on how plant and microbial adaptions to environmental disturbance regulate soil carbon stability, which serves as a self-stabilizing mechanism of natural ecosystems, especially under climate change. Applications of Intelligent Science and Technology, especially systems modeling, digital twins, and parallel intelligence in Cyber Physical Social Systems for sustainability are her main recent interest. She is also interested in effects of anthropogenic activities on plant and microbial adaptions to climate change. She has published more than 200 articles in major scientific journals like PNAS, National Science Review, Global Change Biology and Journal of Ecology. She received the Frist Prize of Science and Technology Award in the Tibet and the Second Prize of Science and Technology Progress Award in Qinghai for her achievement in ecological research on the Qinghai-Tibetan Plateau.
Prof. Sanghamitra Bandyopadhyay did her B Tech, M Tech and Ph. D. in Computer Science from Calcutta University, IIT Kharagpur and Indian Statistical Institute respectively. She then joined the Indian Statistical Institute as a faculty member, and became the Director in 2015. Since 2020 she is continuing in her second tenure as the Director of the Institute. Her research interests include computational biology, soft and evolutionary computation, artificial intelligence and machine learning. She has authored/co-authored several books and numerous articles in journals, book chapters, and conference proceedings and has a citation h-index of 54. Prof. Bandyopadhyay has worked in many Institutes and Universities worldwide. She is the recipient of several awards including the Shanti Swarup Bhatnagar Prize in Engineering Science, TWAS Prize, Infosys Prize, Swarnajayanti fellowship, INAE Silver Jubilee award, INAE Woman Engineer of the Year award (academia), IIT Kharagpur Distinguished Alumni, Humboldt Fellowship from Germany, Senior Associateship of ICTP, Italy, several young engineer/scientist awards, and Dr. Shanker Dayal Sharma Gold Medal and Institute Silver from IIT, Kharagpur, India, She is a Fellow of the Indian National Science Academy (INSA), National Academy of Sciences, India (NASI), National Academy of Engineers (INAE), Institute of Electrical and Electronic Engineers (IEEE), The World Academy of Sciences (TWAS), International Association for Pattern Recognition (IAPR) and West Bengal Academy of Science and Technology.
Prof. Levente Kovács
Taming Cancer: Personalized Cancer therapy by Model-based Control Engineering Methods
Imagine if tumor growth would be reduced and then kept in a minimal and safe volume in an automated manner and in a personalized way, i.e. cancer drug would be injected using a continuous therapy improving the patient’s quality of life.
In conventional cancer therapies the doses are chosen to be as high as possible to maximize the effect of the drug and minimize the chance of the development of drug resistance. However, this approach increases side effects and costs.
Optimization based on mathematical models is a promising direction of personalized medicine. Personalizing, thus optimizing treatments may have multiple advantages, from fewer side effects to lower costs. However, personalization is a complicated process in practice. We discuss a mathematical model of tumor growth and therapy optimization algorithms that can be used to personalize therapies. The therapy generation is based on the concept of keeping the drug level over a specified value. The developed control algorithms can handle inter- and intrapatient variability, positivity, and impulsive nature of the control input. In silico tests proved that our algorithms are suitable for optimizing therapies demonstrated on animal experiments as well. The experimental results show that the introduced algorithms significantly increased the overall survival of the mice, demonstrating that by control engineering methods taming the cancer is realistic possibility.
Prof. Dr. habil. Levente Kovács is full professor of the John von Neumann Faculty of Informatics at Óbuda University, Budapest, Hungary. He also currently serves as rector of the University.
Prof. Kovács has MSc degrees in electrical engineering and in biomedical engineering, and a PhD (2008, from Budapest University of Technology and Economics) with a thesis on control methods for insulin dosage in diabetes. His fields of interest are modern control theory and physiological controls and he published more than 500 articles in these areas.
He is a board member of the Applied Informatics and Applied Mathematics Interdisciplinary Doctoral School and the Habilitation and Doctoral School of Obuda University. He founded the Physiological Controls Research Center at Obuda University in 2013 and is heading it since. He is member of the IFAC TC 8.2 “Biological and Medical Systems” form 2010, member of the IFAC TC 9.4 “Control Education” from 2017, and member of the Hungarian Diabetes Association from 2010, in which he founded and chairs the Hungarian Artificial Pancreas Working Group. He is chair of the Hungary Chapters of IEEE SMC and IEEE Control Society; he chaired the IEEE Hungary Section from 2017 to 2020, and has been re-elected in this role in 2022.
In 2015 Prof Kovacs received the highly prestigious ERC StG grant of the European Union in tumor control that aimed to research the context of personalized tumor control by control engineering methods as a double optimization min-max problem: reducing the therapy cost and maximizing the quality of life. In 2016 he founded the Cyber-Medical Technical Committee of the IEEE SMC Society, promoting the theory and practice of personalized healthcare.
Transdisciplinary Systems Engineering: A 21st Century Systems Engineering Imperative
With ever-increasing complexity of sociotechnical systems, systems engineering is undergoing a historic transformation to increase methodological rigor, flexibility of modeling methods, and exploit the growing convergence of systems engineering with other disciplines. This trend is a key enabler of transdisciplinary systems engineering, which I define as a meta-discipline that exploits the convergence of systems engineering with other disciplines to frame and solve problems that appear intractable when viewed solely through an engineering lens. To illustrate the application of transdisciplinary systems engineering, my talk will focus on exploiting the synergy of Model Based Systems Engineering and Entertainment Arts. Specifically, I will show that by transforming system models into stories that can be executed in virtual worlds, it becomes possible to increase the understanding and participation of all stakeholders, especially in upfront engineering. I will illustrate the use of this approach within the context of a campus security system. I will conclude by reviewing key concepts from other disciplines that can also be exploited in systems engineering to increase system life cycle coverage as well as enhance semantics and flexibility of system modeling approaches.
Azad Madni is a University Professor and holder of the Northrop Grumman Foundation Fred O’Green Chair in Engineering in the University of Southern California’s Viterbi School of Engineering, executive director of USC’s Systems Architecting and Engineering Program, and founding director of the Distributed Autonomy and Intelligent Systems Laboratory. He is founder and CEO of Intelligent Systems Technology, Inc., a high-tech R&D company specializing in transdisciplinary approaches to scientific and societal problems of national and global significance. He is also the chief systems engineering advisor to the Aerospace Corp. and was previously a Distinguished Visiting Fellow at NASA’s Jet Propulsion Laboratory.
Dr. Madni defined the field of transdisciplinary systems engineering and is the creator of TRASEE™, a transdisciplinary engineering education paradigm that fosters out-of-the-box thinking while enhancing retention and recall of concepts and facts through innovative storytelling and role-playing approaches. His key areas of research include transdisciplinary and model-based systems engineering methods for realizing intelligent cyber-physical-human systems (such as autonomous vehicles, smart manufacturing, and outcome-driven health care), interactive storytelling in virtual worlds, and augmented intelligence in adaptive human-machine teaming.
He has served as principal investigator on 97 R&D projects totaling over $100M in funding. Federal sponsors of his research include DARPA, NSF, NASA, DHS, NIST, DOE, and AFOSR, among others; industry sponsors include Boeing, General Motors, Northrop Grumman, Raytheon, Lockheed Martin, and SAIC. He is the author of Transdisciplinary Systems Engineering: Exploiting Convergence in a Hyper-Connected World (Springer, 2018) and coauthor of Tradeoff Decisions in System Design (Springer, 2016). He has authored 19 book chapters and more than 400 peer-reviewed publications, and given more than 75 keynote presentations and invited talks at international conferences, major universities, and government agencies.
He was elected to the National Academy of Engineering in 2021, and has been selected to receive the 2023 IEEE Simon Ramo Medal for pioneering contributions to systems engineering and systems science using interdisciplinary approaches. He received the National Academy of Engineering Bernard M. Gordon Prize for Innovation in Engineering and Technology Education. He is a fellow of ten professional science and engineering societies, including AAAS, IEEE, AIAA, INCOSE, and IISE.
He earned his BS, MS, and PhD degrees in engineering from the University of California, Los Angeles. He is a graduate of AEA/Stanford Executive Institute.
Dr. Fred Hadaegh
Dr. Fred Hadaegh, JPL Fellow and Senior Research Scientist, was NASA Jet Propulsion Laboratory (JPL) Chief Technologist between 2017 and 2022. A subdivision of California Institute of Technology (Caltech), JPL is the lead center for robotic space exploration, with around 6000 employees and a yearly budget exceeding $2.5B.
Dr Hadaegh joined JPL in 1984 after receiving his Ph.D. in Electrical Engineering from the University of Southern California. For over two decades he supervised the Guidance and Control (G&C) Analysis Group, which is responsible for leading research in guidance, estimation, and control theory and developing algorithms and software for planetary science and astrophysics missions. He also previously led the development of G&C technologies for spacecraft formation flying, autonomous rendezvous, and docking for NASA missions and Department of Defense programs.
His research interests include optimal estimation and control as applied to distributed spacecraft. He has published extensively on mathematical modeling of uncertain systems, parameter identifiability of dynamical systems, identification and control of large space structures, and autonomous control of distributed spacecraft systems.
Dr Hadaegh is a Fellow of the Institute of Electronics and Electrical Engineers (IEEE) and Fellow of the American Institute of Aeronautics and Astronautics (AIAA). He has received numerous awards including NASA’s Exceptional Service and Exceptional Achievement Medals, and JPL’s Award of Excellence for “Flight Validation of Autonomous Rendezvous in Earth Orbit.”
Dr. Juan Bernabé-Moreno
When technologies converge to accelerate science and improve the quality of life
-Harnessing the power of HPC, hybrid cloud, Artificial intelligence and Quantum Computing together to increase the pace of new discoveries and improve our quality of life.
The urgency of science has never been stronger. This is driven by the complexity and the scale of the global challenges that we face today and will face tomorrow. Whether we’re dealing with the impact of a new pandemic, or climate change or food shortages or energy security, etc these challenges require us that we act with unprecedented agility and speed.
We need to collectively accelerate the pace of discovery to addressing some of these problems. We must rely on science not only to produce the critical breakthroughs, but also as a rigorous methodology for decision making, and we have one. The process of asking questions then doing research, forming hypotheses, running experiments, testing and sharing with the community is what we know as scientific method. It’s something that works very well, but also that is an elaborate and long-running process, involving a lot of manual work and repetitive tasks, which makes it very expensive to conduct.
Through the convergence of the most salient technologies from the present and the recent past, such as HPC, hybrid cloud, artificial intelligence and quantum computing, we will uncover new ways to accelerate the scientific method to advance tackling the biggest challenges of our time.
Dr. Juan Bernabé-Moreno is the Director of IBM Research Europe, Ireland and UK. with the responsibilities to drive innovation and grow a world-class industrial research organization in AI, Accelerated Discovery, high performance computing, mathematical modeling, quantum computing, and other cutting-edge sciences and technologies.
Juan is a highly recognized leader in data and AI in both academia and industry. Previously to joining IBM Research Europe, he has been the Chief Data Officer and Global Head of Analytics and AI at E.ON, the world’s largest investor-owned energy service provider, leveraging data and algorithms to support the energy transition. He has more than 20 years of experience in the field of data and AI, and has delivered large data transformation programs for top companies in Spain and Germany.
Explainable AI: Reverse engineering solutions with Genetic Programming
Explainable AI: Reverse engineering solutions with Genetic Programming
Historically, AI had to do with rule bases devised by knowledge engineers. Of late, however, the term has come to symbolize an implementation of reinforcement learning and Artificial Neural Networks. Yet this representation in terms of weights and connections is problematic for humans to understand. The need to understand arises not only when we need to more strongly certify the solution; an often ignored need is to know if the problem as posited and solved is the one intended. Current approaches to the explainability layer go by the name of “explainable AI” and rely on simple regressions in limit input spaces, or struggle with creating models which can replicate the black-box behaviour whilst being distillable to an understandable explanation. An alternative, thus far not well explored, is to reverse engineer the black box by means of Genetic Programming. Koza’s original intention was the evolution of computer programs and functions that could provide an understanding because the tools of computer programming are, or should be, familiar to the human. This has great potential to address the shortfalls of existing methods. I will describe an application of Genetic Programming to reverse engineer the neural network. Moreover, one example combines grammars to address a problem of COVID lockdown easement. The talk will discuss challenges to be addressed to deliver capability for the real world, and what can become enabled by such an explainable AI capability, leveraged by these efforts, to be of great value to AI practice.
Daniel Howard holds PhD BS and MSc degrees in chemical and civil engineering. He was the Rolls-Royce Research Fellow in Computational Fluid Dynamics at University of Oxford and, after a spell in the oil industry, joined the then elite UK Defence Evaluation and Research Agency in Malvern, UK (now QinetiQ) where he pioneered and led the AI team that developed Genetic Programming R&D theory and practice, achieving practical and tested deployments of GP solutions to military Computer Vision, Genomics, Medical Image Analysis and Traffic Modelling for the UK Highways Agency (MIDAS system) and achieved the grade of Fellow. He was also rewarded by the 2003 accolade from the then Chief Scientist of Ministry of Defence. Reinstated to the SCR of Pembroke College Oxford in 2002, he was made Honorary Chair Professor at National Taipei University of Technology. Since 2008 he has run his company specializing in bespoke AI software for clients. He developed multirun subtree encapsulation co-publishing the method with John Koza. This is the second well known method of explicit modularization representing the function subprogram in GP – the first is Koza’s ADF (automatically defined functions: parameterized subroutines in GP). Since 2001 he has developed a method that uses GP trees to create vectors of numbers that are then interpreted by a user specified grammar and has deployed these for reverse engineering neural networks and other applications.
Autonomous AI and Symbiotic Human-Machine Intelligence Systems
Autonomous AI (AAI) and Symbiotic Human-Machine Intelligence Systems
It is recognized that the general form of Artificial Intelligence (AI), equivalent to human Natural Intelligence (NI), is Autonomous AI (AAI) underpinned by Intelligence Science, Brain-Inspired Systems (BIS), Cognitive Computers (kC) , Intelligent Mathematics (IM), as well as System, Man, and Cybernetics.
This talk presents basic research on fundamental theories, discoveries, and the latest development in AAI and Symbiotic Human-Machine Intelligence Systems (SHMIS) It is revealed that the ultimate aim of AAI is not pre-trained nor pre-programmed intelligence, because both classical approaches may not generate cognitive and autonomous intelligence as that of the brain beyond those of adaptive, imperative, and reflexive intelligence according to the Hierarchical Intelligence Model (HIM) of intelligence science. It explains why the reinforcingly trained Chat-GPT may not carry out inductive reasoning and deductive intelligence generation centric in NI. It explains the difference between machine knowledge (memorization-based) and machine intelligence (reasoning-and-creativity-based). For instance, a trained AI system may memorize an entire encyclopedia, but it may not sufficiently be intelligent for enabling machinable thinking and inference as that of human brains.
This talk queries the intelligent and sociological impacts of AAI towards the Symbiotic Human-Robot Society (SHRS). In SHRS, humans and intelligent robots work symbiotically in a hybrid society that will lead to: a) Sharable wisdoms for coherent intelligence generation for real-time problem solving and decision making; b) Downloadable knowledge acquisition free from learning; c) Mutual augmentation between human and machine intelligence based on their complemental advances. Therefore, SHRS will form a Symbiotic Intelligent Operating Framework (SIOF) for synergizing the advanced inductive reasoning power of humans and the fast knowledge/information processing capability of machines in a coherent platform in order to enable unprecedent human intelligence and unlimited human creativity.
Dr. Yingxu Wang is professor of intelligence science, brain science, autonomous systems, software science, and intelligent mathematics. He is the founding President of Int’l Institute of Cognitive Informatics and Cognitive Computing (I2CICC). He is FIEEE, FBCS, FI2CICC, FAAIA, FWIF, and P. Eng. He has held visiting professor positions at Univ. of Oxford (1995, 2018-2023), Stanford Univ. (2008, 2016), UC Berkeley (2008), MIT (2012), and a distinguished visiting professor at Tsinghua Univ. (2019-2022). He received a PhD in Computer Science from Nottingham Trent University, UK, in 1998 and has been a full professor since 1994. He is the founder and steering committee chair of IEEE Int’l Conference Series on Cognitive Informatics and Cognitive Computing (ICCI*CC) since 2002. He is founding Editor-in-Chiefs and Associate Editors of 10+ Int’l Journals and IEEE Transactions, particularly EiC of IEEE SMC Letters. He is Chair of IEEE SMCS TC-BCS on Brain-inspired Cognitive Systems, Co-Chair of IEEE CS TC-CLS on Computational Life Science, and the steering committee representative of IEEE Computer Science to the Computational Intelligence Society’s Tarns. on Cognitive and Development Systems.
His basic research has spanned across contemporary scientific disciplines of intelligence, mathematics, knowledge, robotics, computer, information, brain, cognition, software, data, systems, cybernetics, neurology, and linguistics. He has published 600+ peer reviewed papers and 38+ books/proceedings. He has presented 70+ invited keynote speeches to international conferences. He has served as honorary, general, and program chairs for 40+ international conferences. He has led 10+ international, European, and Canadian research projects as PI. He is recognized by Google Scholar as world top 1 in Software Science, top 1 in Cognitive Robots, top 8 in Autonomous Systems, top 2 in Cognitive Computing, and top 1 in Knowledge Science with an h-index 67. He is recognized by ResearchGate as among the world’s top 1.0% scholars in general and in several contemporary fields encompassing artificial intelligence, autonomous systems, theoretical computer science, engineering mathematics, software engineering, cognitive science, information science, and computational linguistics. He has created and/or formally proved 100+ theorems in the aforementioned transdisciplinary fields, encompassing two of the world’s top ten hardest mathematical problems known as the Goldbach conjecture and Twin-Prime conjecture in 2022.
James Ayinde Fabunmi
From Brain Power to Economic Power
* Forum on development of knowledge based societies *
Dr. James A. Fabunmi obtained his Ph.D. in Aeronautical Engineering from the Massachusetts Institute of Technology (MIT) in 1978, and has been a Research Engineer at Kaman Aerospace Corporation, Faculty member of Aerospace Engineering at University of Maryland College Park, Founder/Owner of the Advanced Engineering Design and Research (AEDAR) Corporation and Consultant to Major Industry, Government Agencies, Innovation Companies and Universities. He has provided scientific and technical advisory services to various program elements of the United States Department of Defense, and developed initiatives and participated in the conduct of Scientific and Engineering Research and Development in collaboration with Industry, Academia and Government. He is currently the Chief Operating Officer of the American Heritage Defense Corporation (AHDC), a Washington DC 501(c)3 think tank engaged in consulting and advocacy on innovation driven entrepreneurship and diversity. He is the founder of the Adulawo Institute and a co-founder of AWENI the Association of Western Nigeria Innovators – “The Game Changers” for Innovation and Economic Development of Western Nigeria. He is the author of the book “From Brain Power to Economic Power” available on Amazon at: