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Keynote Speaker-ICRCV 2023

 

Prof. Bir Bhanu (IEEE Fellow, AAAS Fellow, SPIE Fellow)

Marlan and Rosemary Bourns Presidential
Endowed Chair and Distinguished Professor
University of California, Riverside, USA

Biography: Bir Bhanu is the Distinguished Professor of Electrical and Computer Engineering, Marlan and Rosemary Bourns Endowed University of California Presidential Chair in Engineering and has served as the founding Director of the Center for Research in Intelligent Systems (CRIS) for over 21 years at the University of California, Riverside (UCR). He was the first Founding Faculty of the Bourns College of Engineering (BCOE) at UCR and the Founding Chair of Electrical Engineering which was the first program in engineering. Prior to joining UCR, he was a Senior Fellow at Honeywell Inc. He has pioneered the areas of 3D object, target and human (ear, gait, face, fingerprint) recognition; machine learning in computer vision; dynamic scene analysis and motion understanding, synthesis of recognition systems; human relevance feedback for image database queries; and video bioinformatics. With 12 books (seven authored and five edited), more than 180 long journal papers, 386 reviewed conference papers, 58 book chapters, 16 special issues of top journals and 18 patents, he has advanced the areas of computer vision, machine intelligence, bioinformatics and biometrics. He has served as associate editor of over a dozen journals and many panels and advisory boards. He has received many outstanding journal and conference paper awards with his students. He has demonstrated a highly prolific spirit of innovations and has been an inspiring teacher and mentor who has supervised 42 PhD students, 40 MS students and 22 Post-docs. He was honored with the UC-Riverside Dissertation Advising/Mentoring Award (2011). He has been the principal investigator of many programs from NSF, DoD, DARPA, IARPA, NASA and other U.S. agencies and industries. He received several research excellence and outstanding contributions awards from the university and industries (Honeywell and IBM). He received the Research Excellence Award from the UCR BCOE in 2003 and the Pioneer Award in 2015. Recently he was honored with the Faculty Research Lecturer Award (2019), UCR Academic Senate’s highest Award for Faculty Research (the first such award to a faculty in Bourns College of Engineering since its inception 32 years ago). He holds a B.S. (with Honors) in Electronics Engineering from the Indian Institute of Technology (IIT), BHU; an M.E. (with Distinction) in Electronics Engineering from the Birla Institute of Technology and Science (BITS), Pilani; S.M. and E.E. degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT), Cambridge, MA; Ph.D. in Electrical Engineering from the University of Southern California (USC), Los Angeles and M.B.A. from the University of California, Irvine (UCI). He is a Fellow of IEEE, AAAS, IAPR, SPIE, AIMBE and NAI.

Speech Title: Perception and Learning for Intelligent Systems
Abstract: As intelligent machines begin to venture from the research laboratory into the real world, they must possess skills similar to those of humans to perform effectively. At a high level, these skills can be divided into two groups: (1) the ability to sense the world or the environment in which they operate (machine perception), and (2) the ability to understand and react to that sensory input (machine intelligence). Systems which lack either of these abilities cannot be considered truly robust. Bhanu has spent the last four decades in the research and development of robust autonomous systems with multi-modal sensing capabilities which are able to perform intelligent tasks and interact with other biological and artificial systems. This journey has taken him from developing foundational predictive theory of object recognition to the fusion of model and data driven methods to purely data driven deep learning methods for a wide variety of practical applications such as object/target/human/species recognition, total vehicle modeling and recognition/identification for security and intelligent transportation. This talk will present challenges and effective solutions with examples of disciplinary and interdisciplinary projects for a range of diverse applications.

Prof. Qing-Long Han (FIEEE, FIFAC, FIEAust, FCAA)

Distinguished Professor
Pro Vice-Chancellor (Research Quality)
Swinburne University of Technology, Australia

Biography: Professor Han is Pro Vice-Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology, Melbourne, Australia. He held various academic and management positions at Griffith University and Central Queensland University, Australia.
Professor Han was awarded The 2021 Norbert Wiener Award (the Highest Award in systems science and engineering, and cybernetics), The 2021 M. A. Sargent Medal (the Highest Award of the Electrical College Board of Engineers Australia), The IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award in 2022, 2020, and 2019, respectively, The IEEE/CAA Journal of Automatica Sinica Norbert Wiener Review Award in 2021, and The IEEE Transactions on Industrial Informatics Outstanding Paper Award in 2020.
Professor Han is a Member of the Academia Europaea (The Academy of Europe). He is a Fellow of The Institute of Electrical and Electronics Engineers (FIEEE), a Fellow of The International Federation of Automatic Control (FIFAC), a Fellow of The Institution of Engineers Australia (FIEAust), and a Fellow of The Chinese Association of Automation (FCAA). He is a Highly Cited Researcher in both Engineering and Computer Science (Clarivate Analytics). He has served as an AdCom Member of IEEE Industrial Electronics Society (IES), a Member of IEEE IES Fellows Committee, a Member of IEEE IES Publications Committee, and Chair of IEEE IES Technical Committee on Networked Control Systems. He is currently the Editor-in-Chief of IEEE/CAA Journal of Automatica Sinica, the Co-Editor-in-Chief of IEEE Transactions on Industrial Informatics, and the Co-Editor of Australian Journal of Electrical and Electronic Engineering.

Speech Title: Resource-Efficient and Secure Automated Vehicle Platoons
Abstract: 
Vehicle platooning has been regarded as a promising intelligent transportation system technology for achieving cooperative automated driving systems and automated highway systems due to its promising benefits, including improved road safety, highway capacity and traffic congestion relief, and reduced fuel consumption. Two critical challenges of accomplishing automated vehicle platoons are: 1) to deal with the intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources; and 2) to tackle the malicious cyber-attacks on the vehicle-to-vehicle communication channels.
The essentials of evolutionary platooning control technologies are first introduced for connected automated vehicles. After a brief historical background of connected automated vehicles and vehicle platooning, several key issues in the design and implementation of an automated vehicle platooning control system are elaborated. An emphasis is then placed on two emerging platooning control techniques: resource-efficient vehicle platooning and secure vehicle platooning. Furthermore, simulation and validation results under these two control techniques are presented. Finally, some challenging issues and concluding remarks are drawn.

 

Prof. Darwin Caldwell (FREng, IEEE Fellow)

Founding Director
Italian Institute of Technology, Italy

Biography: Darwin G Caldwell is Founding Director of the Istituto Italiano di Tecnologia (IIT) in Genova, and Director of the Dept. of Advanced Robotics (ADVR) at IIT. He holds a B.Sc (1986) and Ph.D. (1990) in Robotics from the University of Hull and an M.Sc in Management (1996) from the University of Salford.   He has pioneered developments in compliant and variable impedance actuation, Soft and Human Friendly Robotics and the creation of 'softer', safer robots, that draw on developments in materials, mechanisms, sensing, actuation and software. These developments have been fundamental to advances in humanoids, quadrupeds, medical robotics and exoskeletons. Key robots developed by his team include: iCub, a child-sized humanoid robot; COMAN, a controllably compliant humanoid designed to safely interact with people and have more natural (loco)motion; WALK-MAN, a 1.85m tall, 120kg humanoid that competed in the DARPA Robotics Challenge; the HyQ series (HyQ, HyQ2Max, HyQ-Real) of high performance hydraulic quadrupedal robots; and PHOLUS/Centauro, a human-robot symbiotic system capable of robust locomotion and dexterous manipulation in rough terrain and harsh environments. In addition to his research in legged robots, Prof. Caldwell also works extensively to develop wearable and haptic systems including whole body exoskeletons such as the XoSoft, XoTrunk, XoShoulder and XoElbow and in surgical and rehabilitation robotics where his team have developed systems such as the CALM (Computer Aided Laser Microsurgery) systems, the Cathbot, Cathbot-Pro and SVEI (for catherization and tissue type detection) and the Arbot (Ankle rehabilitation robot).
Caldwell is or has been an Honorary professor at the Universities of Manchester, Sheffield, Bangor and King's College London in the UK, and Tianjin University in China. He has published over 700 papers, has over 25 patents and has received over 50 awards/nominations at international conferences and events. He is a Fellow of the Royal Academy of Engineering (FREng - UK’s National Academy) and the IEEE (FIEEE)  and a Chartered Engineer (CEng).

Speech Title: Occupational Exoskeletons
Improving Worker Health, while creating Healthier, more Productive Work Environments

AbstractRisks of work related injury, or even death, have been common throughout history. As long ago as the 18th century Bernardino Ramazzini, an Italian physician, scientist, academic and writer, in his treatise “De Morbis Artificum Diatriba” (Diseases of Workers), provided suggestions for preventing injuries in over 50 types of employment.
Ensuring worker health and safety is now deeply embedded in all work environments, yet according to the World Health Organization (WHO), approximately 1.71 billion people suffer from Work Related Musculo-Skeletal Diseases (WRMSD). And these WRMSDs are not just confined to the more obvious heavy lifting (Manual Material Handling) jobs. It affects workers in all domains from manufacturing, construction and logistics, to office and shop workers and healthcare professionals. As a result, every year more than 40% of workers suffer from lower back or neck/shoulder pain. This makes Musculo-Skeletal Disorders (MSD), the leading cause of work-related health problems. This has important impacts on the worker, their employer, and society in general, due to: sickness absence, injuries and disability, increased costs, higher employee turnover, and lower productivity. It can lead to injuries that can have a lifelong debilitating effect. In the EU it is estimated that 2% of GDP is lost due to WRMSDs.
To mitigate these conditions recent years have seen increasing interest among all stakeholders (e.g. research institutions, national and international health and safety organisations, workers, and companies) in the use of wearable assistive devices and occupational exoskeletons (OEs) that can transfer high (damaging) loads away from critically activated joints and muscles by providing both additional mechanical power and support. In so doing they can improve muscle endurance and potentially reduce or prevent injuries. 
This presentation will explore the background to WRMSDs, and the global development of occupational exoskeletons for manufacturing, and related industries such as automotive, assembly/disassembly, transportation systems, construction, logistics, aviation, and healthcare, that are now starting to see the opportunities for various forms of exoskeletons and assistive devices.  Subsequently, I will focus on exoskeletal and wearable technologies developed at IIT, exploring the factors influencing their design and operation, and their potential uses, benefits and the challenges to be overcome to fully exploit and benefit from occupational exoskeletons. I shall show that scenario tailored software is a critical feature of the systems design, and I shall demonstrate how this can be applied in real world applications. Finally, I shall consider the future need and potential of this critical technology

Prof. Anouck Girard

University of Michigan, USA

Biography: Anouck Girard received the Ph.D. degree in ocean engineering from the University of California, Berkeley, CA, USA, in 2002. She has been with the University of Michigan, Ann Arbor, MI, USA, since 2006, where she is currently a Professor of Robotics and Aerospace Engineering, and the Director of the Robotics Institute.
She has co-authored the book Fundamentals of Aerospace Navigation and Guidance (Cambridge University Press, 2014). Her current research interests include vehicle dynamics and control, as well as decision systems. Dr. Girard was a recipient of the Silver Shaft Teaching Award from the University of Michigan and a Best Student Paper Award from the American Society of Mechanical Engineers and was a Fulbright Scholar in the Dynamic Systems and Simulation Laboratory at the Technical University of Crete in 2022. She is currently a member of the National Academy of Engineering Committee on Using Machine Learning in Safety-Critical Applications: Setting a Research Agenda.

Speech Title: Safe Autonomy in the Age of Machine Learning

Abstract: Modern autonomous systems face ever-more demanding performance requirements and mission objectives, that must be traded for safety and cost considerations. Common practice is to operate conservatively and avoid violation of safety limits in the worst-case scenario. This ensures safety but can limit autonomous system availability and performance.
Recent advances in machine learning have led to the development of ML-based models and controllers for autonomous systems, including some based on unsupervised learning and/or LLMs. As of now, we have no effective method for assessing the systematic correctness of ML models or controllers. This motivates the development of add-on safety-supervisors, capable of determining whether a system is operating in its operational design domain, and of limiting outputs of the ML system if not.
This talk focuses on novel, emerging approaches to increased autonomy through the design of application domain specific safety supervisors. The potential for applications to control of automotive vehicles and autonomous spacecraft will be highlighted.