Mirjana Ivanovic holds the position of Full Professor at Faculty of Sciences, University of Novi Sad, Serbia. She is author or co-author of 14 textbooks, several monographs and more than 350 research papers, most of which are published in international journals and conferences. She is a member of the University Council for Informatics.

  Her research interests include agent technologies, intelligent techniques (CBR, data and web mining) and their applications, effects and applications of various data mining and machine learning algorithms, programming languages and software tools, e-learning and web-based learning. She is/was a member of Program Committees of more than 250 international conferences, Program/General Chair of several international conferences, and leader of numerous international research projects. Mirjana Ivanovic delivered several keynote speeches at international conferences, and visited numerous academic institutions all over the world as visiting researcher. Currently she is Editor-in-Chief of the Computer Science and Information Systems journal. (e-mail: mira@dmi.uns.ac.rs).

Title:The Role of Agent Technologies in Personalized Medicine
Abstract:  Remarkable gains in life expectancy and declines in fertility have led current society to an ageing global population. On the other hand there is significant number of disabled people who needs adequate medical support. Accordingly numerous researcher communities, stakeholders, and policy makers invest serious efforts to support development of ambient assisted living, smart and intelligent environments that have to facilitate independent living of old and disabled population. Rapid, fascinating, and challenging development in ICT offers wide range of new technologies to facilitate these efforts. Rich complex data collected from living environment could be analyzed in order to discover the patient's preferences, traits, and states. Current multidisciplinary research efforts are oriented towards developing personalized and sophisticated e-coaching facilities to boost adequate recommendations and advices to increase patients’ wellbeing.
 Among other artificial intelligence techniques, agent technologies significantly influence development of intelligent and smart architectures and tools in medical domains. The use of agents and multi agent systems opened the ways to find out new applications like personalized and socialized medical platforms and systems with tailored recommendation capabilities. In this presentation different opportunities and challenges that agent technologies offer in personalized medicine are discussed.

 Dr. Donghui Zhang is the US Head of Translational Medicine and US Head of Nonclinical Efficacy & Safety Biostatistics at Sanofi. She has over 25 years of pharmaceutical industry experiences at Merck and Sanofi, respectively. She has led many projects that successfully yielded drugs that helped patients with multiple sclerosis, asthma, immuno-diseases, diabetes and cancers. She also led the developments of a number of automated big data analytical tools that are used worldwide within companies at different sites. She is currently working on genomic/genetic understanding of some most challenging/rare diseases, e.g., Lupus, Parkinson, and Oncology. She has more than 40 publications in peer reviewed informatics and scientific journals. She received bachelor degree in Electronics from Shandong University and MA and Ph.D. from Rutgers University in Statistics. She also taught various undergraduate and graduate courses at the City College of New York (CCNY) and Rutgers University as an Adjunct Professor.

Title:  Informatics in Drug Discovery and Development- Challenges and Opportunities  
Abstract:  New drug discovery and development are a lengthy, costly and challenging process from target identification to product launching and post market follow up. This talk will provide high level overview of various steps in a drug discovery process, together with some details of scientific objectives and scientific approaches in each step. Informatics plays an important role in this process: big data are generated along the drug discovery and development to understand disease characters, and to select right patient population in terms of treatment safety and efficacy. The informatics and statistics issues involved and how data scientists can contribute significantly to the whole process are presented.  

 MengChu Zhou received his B.S. degree in Control Engineering from Nanjing University of Science and Technology, Nanjing, China in 1983, M.S. degree in Automatic Control from Beijing Institute of Technology, Beijing, China in 1986, and Ph. D. degree in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, NY in 1990. He joined New Jersey Institute of Technology (NJIT), Newark, NJ in 1990, and is now a Distinguished Professor of Electrical and Computer Engineering. His research interests are in Petri nets, intelligent automation, Internet of Things, big data, web services, and intelligent transportation. He has over 700 publications including 12 books, 400+ journal papers (300+ in IEEE transactions), 12 patents and 28 book-chapters. He is the founding Editor of IEEE Press Book Series on Systems Science and Engineering and Editor-in-Chief of IEEE/CAA Journal of Automatica Sinica. He is a recipient of Humboldt Research Award for US Senior Scientists from Alexander von Humboldt Foundation, Franklin V. Taylor Memorial Award and the Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society, and Distinguished Service Award from IEEE Robotics and Automation Society. He is a life member of Chinese Association for Science and Technology-USA and served as its President in 1999. He is presently VP for Conferences and Meetings, IEEE Systems, Man and Cybernetics Society. He is a Fellow of The Institute of Electrical and Electronics Engineers (IEEE), International Federation of Automatic Control (IFAC), American Association for the Advancement of Science (AAAS) and Chinese Association of Automation (CAA).

Title:  What is the Next Industrial Revolution?  
Abstract:  Human beings have experienced two major industrial revolutions. The first one took place in the 19th century, which replaced muscle power from humans and animals with mechanical power. The second one started in the middle 20th century, which provided people and societies with Internet. It was built with the technologies from computing, communication, networking and information storage. Both offered unprecedented productivity increases. What will be the next one? This talk intends to answer this question by presenting some recent development of Internet of Things (IoT) and smart systems. IoT was selected by IEEE as a major initiative to develop and advance over the next few years. Several recent studies have predicted the huge growth of IoT and tremendous benefits to the world economy. It was expected that 26 billion IoT units would be installed by year 2020, generating $300 billion in revenue. The IoT will generate an additional $1.9 trillion in economic value. We plan to present a system engineering approach to Internet-of-Things-based smart systems and their applications to smart manufacturing, smart cities, smart gird, smart medical and healthcare services.  

School of Electrical & Electronic Engineering
Nanyang Technological University
Singapore

    Dr. Lipo Wang received the Bachelor degree from National University of Defense Technology (China) and PhD from Louisiana State University (USA). His research interest is intelligent techniques with applications to optimization, communications, image/video processing, biomedical engineering, and data mining. He is (co-)author of 300 papers, of which 100 are in journals. He holds a U.S. patent in neural networks and a patent in systems. He has co-authored 2 monographs and (co-)edited 15 books. He was keynote speaker for 30 international conferences. He is/was Associate Editor/Editorial Board Member of 30 international journals, including 3 IEEE Transactions, and guest editor for 10 journal special issues. He was a member of the Board of Governors of the International Neural Network Society, IEEE Computational Intelligence Society (CIS), and the IEEE Biometrics Council. He served as CIS Vice President for Technical Activities and Chair of Emergent Technologies Technical Committee, as well as Chair of Education Committee of the IEEE Engineering in Medicine and Biology Society (EMBS). He was President of the Asia-Pacific Neural Network Assembly (APNNA) and received the APNNA Excellent Service Award. He was founding Chair of both the EMBS Singapore Chapter and CIS Singapore Chapter.

    Jie Huang studied at Fuzhou University (Diploma, 1980), Nanjing University of Science and Technology (Master, 1982), and the Johns Hopkins University (PhD, 1990), respectively. He is now Choh-Ming Li Professor of Mechanical and Automation Engineering and Chairman of the Department of Mechanical and Automation Engineering, the Chinese University of Hong Kong. His research interests include automatic control, robotics and automation, and guidance and control of flight vehicles. He authored three monographs and some papers. He received China State Natural Science Award, Class II, in 2010, and Croucher Senior Research Fellowship award in 2006. He is a Fellow of IEEE, IFAC, CCA and HKIE.

    Jie Huang is / was associate editor, subject editor, guest editor, or editor-in-large of over 10 journals. He was Distinguished Lecturer of IEEE Control Systems Society from 2005 to 2008, a member of the Board of Governors of IEEE Control Systems Society from 2006 to 2007. He served as a Science Advisor to the Leisure and Cultural Services Department of Hong Kong Special Administrative Region, and Honorary Advisor to Hong Kong Science Museum.

 MengChu Zhou received his B.S. degree in Control Engineering from Nanjing University of Science and Technology, Nanjing, China in 1983, M.S. degree in Automatic Control from Beijing Institute of Technology, Beijing, China in 1986, and Ph. D. degree in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, NY in 1990. He joined New Jersey Institute of Technology (NJIT), Newark, NJ in 1990, and is now a Distinguished Professor of Electrical and Computer Engineering. His research interests are in Petri nets, intelligent automation, Internet of Things, big data, web services, and intelligent transportation. He has over 700 publications including 12 books, 400+ journal papers (300+ in IEEE transactions), 12 patents and 28 book-chapters. He is the founding Editor of IEEE Press Book Series on Systems Science and Engineering and Editor-in-Chief of IEEE/CAA Journal of Automatica Sinica. He is a recipient of Humboldt Research Award for US Senior Scientists from Alexander von Humboldt Foundation, Franklin V. Taylor Memorial Award and the Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society, and Distinguished Service Award from IEEE Robotics and Automation Society. He is a life member of Chinese Association for Science and Technology-USA and served as its President in 1999. He is presently VP for Conferences and Meetings, IEEE Systems, Man and Cybernetics Society. He is a Fellow of The Institute of Electrical and Electronics Engineers (IEEE), International Federation of Automatic Control (IFAC), American Association for the Advancement of Science (AAAS) and Chinese Association of Automation (CAA).

 

 Ngoc Thanh Nguyen is a full professor of Wroclaw University of Science and Technology, and the Head of Information Systems Department in the Faculty of Computer Science and Management. His scientific interests consist of collective intelligence, knowledge integration methods, inconsistent knowledge processing, and multi-agent systems. He has edited more than 30 special issues in international journals, 52 books and 35 conference proceedings. He is the author or co-author of 5 monographs and more than 350 journal and conference papers. Prof. Nguyen serves as Editor-in-Chief of International Journal of Information and Telecommunication (Taylor&Francis), Transactions on Computational Collective Intelligence (Springer) and Vietnam Journal of Computer Science (Springer). He is also an Associate Editor of several prestigious international journals. He was a General Chair or Program Chair of more than 40 international conferences. He serves as an expert of National Center of Research and Development and European Commission in evaluating research projects in several programs like Marie Sklodowska-Curie Individual Fellowships, FET and EUREKA. He has given 20 plenary and keynote speeches for international conferences, and more than 40 invited lectures in many countries. In 2009 prof. Nguyen was granted of title Distinguished Scientist of ACM. He was also a Distinguished Visitor of IEEE and a Distinguished Speaker of ACM. Now he is serving as the Chair of IEEE SMC Technical Committee on Computational Collective Intelligence.

 

 Daoyi Dong is currently an Associate Professor and Scientia Fellow at the University of New South Wales, Canberra, Australia. He was with the Chinese Academy of Sciences and with the Zhejiang University. He had visiting positions at Princeton University, NJ, USA, RIKEN, Wako-Shi, Japan and The University of Hong Kong, Hong Kong. He received a B.E. degree in automatic control and a Ph.D. degree in engineering from the University of Science and Technology of China, Hefei, China, in 2001 and 2006, respectively. His research interests include quantum systems control, multiagent systems and machine learning. Prof. Dong was awarded an ACA Temasek Young Educator Award by The Asian Control Association and is a recipient of an International Collaboration Award, a Discovery International Award and an Australian Post-Doctoral Fellowship from the Australian Research Council, and Humboldt Research Fellowship from Alexander von Humboldt Foundation in Germany. He is also a co-recipient of several Best Paper Awards at various international conferences. He serves as an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems. He is the Chair of Technical Committee on Quantum Cybernetics, IEEE Systems, Man and Cybernetics Society (SMCS), the Chair of IEEE SMC ACT Chapter, and the Coordinator of Conference and Meeting Committee, IEEE SMCS. He has also served as General Chair or Program Chair for several international conferences. He has published more than 75 journal papers in leading journals, more than 50 conference paper, and one book. He has attracted a number of competitive grants with more than AU$2 million from Australia, USA, China and Germany.

 

 Through several waves of ups and downs in the past decades, artificial intelligence (AI) has evolved into a must-have new technology or tool in various domains. Furthermore, with the advent of powerful GPU, AI-related research or AI-based applications have sprouted in every corner of the world. Originating from pure network connectivity, the Internet of Things (IoT) has become a structure that can collect every piece of data from physical devices, daily activities, images, or videos into a data reservoir. As a result, tons of data are automatically generated into an enterprise database in a single day. This creates research opportunities on integrating AI, IoT, big data, and cloud or edge computing, to improve the quality of industrial production or medical service. Applications of AI algorithms, models, or techniques play important roles and can be found everywhere, including widespread usage in industry and medical systems for tasks such as locating and detecting scratches or defects in product surface, printed circuit board manufacturing, monitoring rehabilitation progress for patients with Parkinson’s disease or stroke, autonomous moving and planning of service robots in healthcare, and short-term or long-term prediction of air quality in certain areas. Furthermore, AI can be integrated with other techniques, such as Internet of things, big data, cloud computing, and edge computing to become powerful tools for industry and medicine domains. This talk will address from the AIoT, and system engineering perspective for applications faced in industry and healthcare.

 

 This presentation covers research topics in Intelligent Robotics, tele-operation and haptics. Through a series of case studies, it demonstrates integration of haptic (tactile sensing) technology into augmented and virtual reality (AR/VR) systems, to increase their fidelity and realism for simulation-based training applications. The concept of robot based motion simulators will highlight the advanced capabilities of an in-house developed Universal Motion Simulators (UMS) series. UMS as the next generation of vehicle simulation, features a far greater range of motion, greater flexibility and more realism. It has proved to be a reliable, safe and cost-effective simulator that can realistically emulate the driving, riding and flying experience of a range of land, air, sea and space vehicles.

 

 Peng Shi received the PhD degree in Electrical Engineering from the University of Newcastle, Australia, the PhD degree in Mathematics from the University of South Australia, the Doctor of Science degree from the University of Glamorgan, UK, and the Doctor of Engineering degree from the University of Adelaide, Australia. He is now a Distinguished Professor at the School of Electrical and Mechanical Engineering, and the Director of Advanced Unmanned Systems Laboratory, at The University of Adelaide, Australia. His research interests include systems and control theory and applications to autonomous and robotic systems, cyber-physical systems, and multi-agent systems. He received the Ramesh Agarwal Life-time Achievement Award in Science, Engineering and Technology from the International Engineering and Technology Institute in 2023, the Meritorious Service Award from IEEE Systems, Man and Cybernetics Society in 2023, the MA Sargent Medal Award from Engineers Australia in 2022; the recognition of Life-time Achiever Leaderboard and Field Leader from The AUSTRALIAN Research Review from 2019-2023, and the acknowledgement of a Highly Cited Researcher from Thomson Reuters consecutively since 2014. Currently he serves as the Editor-in-Chief of IEEE Transactions on Cybernetics, a Senior Editor of IEEE Access, and an editorial member for journals, including Automatica and IEEE Transactions on (Artificial Intelligence, and Circuits and Systems-I). His professional services also include as the President of the International Academy for Systems and Cybernetic Sciences (2021--), the Vice President of IEEE SMC Society (2021-2022), and IEEE SMC Society Distinguished Lecturer (2020--). He is a Fellow of IEEE, IET, IETI, IEAust and CAA, a Member of the Academy of Europe.

 

 Professor Chin-Chen Chang has worked on many different topics in information security, cryptography, multimedia image processing and published several hundreds of papers in international conferences and journals and over 38 books. He was cited over 48,533 times and has an h-factor of 100 according to Google Scholar. Several well-known concepts and algorithms were adopted in textbooks. He also worked with the National Science Council, Ministry of Technology, Ministry of Education, Ministry of Transportation, Ministry of Economic Affairs and other Government agencies on more than 100 projects and holds 34 patents, including one in US and nineteen in China. He served as Honorary Professor, Consulting Professor, Distinguished Professor, Guest Professor at over 60 academic institutions and received Distinguished Alumni Award's from his Alma Master's. He also served as Editor or Chair of several international journals and conferences and had given almost a thousand invited talks at institutions including Chinese Academy of Sciences, Academia Sinica, Tokyo University, Kyoto University, National University of Singapore, Nanyang Technological University, The University of Hong Kong, National Taiwan University and Peking University. Professor Chang has mentored 7 postdoctoral, 68 PhD students and 208 master students, most of whom hold academic positions at major national or international universities. He has been the Editor-in-Chief of Information Education, a magazine that aims at providing educational materials for middle-school teachers in computer science. He is a leader in the field of information security of Taiwan. He founded the Chinese Cryptography and Information Security Association, accelerating information security the application and development and consulting on the government policy. He is also the recipient of several awards, including the Top Citation Award from Pattern Recognition Letters, Outstanding Scholar Award from Journal of Systems and Software, and Ten Outstanding Young Men Award of Taiwan. He was elected as a Fellow of IEEE in 1998, a Fellow of IET in 2000, a Fellow of CS in 2020, an AAIA Fellow in 2021, a Member of the Academy of Europe (AE) and a Member of the European Academy of Sciences and Arts (EASA) for his contribution in the area of information security. In 2023, he was awarded the Honorary Ph.D. Degree in Engineering, National Chung Cheng University, Taiwan.

 

 Dr. Sos Agaian is a Distinguished Professor of Computer Science at the Graduate Center and the College of Staten Island, CUNY. Before joining CUNY, he was the Peter T. Flawn Professor at the University of Texas at San Antonio. He also served as a Visiting Professor at Tufts University and a Lead Scientist at Aware, Inc. in Boston, Massachusetts. His research spans computational vision, machine learning, AI, multimedia security, remote sensing, and biomedical imaging. Dr. Agaian has received funding from NSF, DARPA, Google, and other agencies. He has published over 850 articles, 10 books, and 19 book chapters and holds 56 patents/disclosures, many of which have been licensed. He has mentored 45 PhD students and received multiple awards for research and teaching, including the MAEStro Educator of the Year, the Distinguished Research Award, the Innovator of the Year, the Tech Flash Titans-Top Researcher Award, and recognition as an Influential Member of the School of Engineering at Tufts University. He is an Associate Editor for several journals, including the IEEE Transaction of Cybernetics. He is a fellow of the Society for Imaging Science and Technology (IS&T), the Optical Society of America (SPIE), the American Association for the Advancement of Science (AAAS), Institute of Electrical and Electronics Engineers (IEEE), The Asia-Pacific Artificial Intelligence Association (AAIA), and Member of Academia Europaea. He has delivered over 35 keynote speeches and 100 invited talks and co-founded/chaired over 200 international conferences. He has also been a Distinguished IEEE Systems, Man, and Cybernetics Society Lecturer.

Title: Bio-Inspired No-Reference Image Quality Assessment: From Human Visual Systems to Computational Models

Abstract: Image Quality Assessment (IQA) poses a significant challenge in computer vision, especially without reference images. While traditional metrics such as Mean Squared Error (MSE) have been prevalent in the field, their correlation with human perception is still limited. This keynote presents a comprehensive framework for no-reference (blind) IQA using bio-inspired computational models that connect human and machine vision systems. By incorporating computational neuroscience and cognitive science insights, our approach emulates key human visual system characteristics to create more perceptually accurate quality metrics. We illustrate how bio-inspired architectures can effectively evaluate image quality across various distortions encountered during image acquisition, compression, transmission, and storage, surpassing conventional metrics in alignment with human judgments. The presentation will address fundamental questions about the limitations of MSE-based approaches and introduce novel bio-inspired solutions for blind IQA. We present recent breakthroughs in our research, including new computational models that achieve state-of-the-art performance on standard IQA benchmarks while maintaining biological plausibility. These advances improve quality assessment accuracy and provide insights into the underlying mechanisms of human visual perception. Our findings have significant implications across multiple domains, from consumer photography and video streaming to medical imaging and computer vision systems. The talk will conclude with a discussion of future research directions and the potential impact of bio-inspired IQA on emerging visual technologies.

 Short Bio: Henry Leung is a Schulich Industry Research Chair Professor of the Department of Electrical and Software Engineering at the University of Calgary, Canada. His current research interests include data analytic, information fusion, machine learning, signal and image processing, robotics, and internet of things. He has published over 350 journal papers and 250 refereed conference papers. Dr. Leung has been the associate editor of various journals such as the IEEE Circuits and Systems Magazine, International Journal on Information Fusion, IEEE Trans. Aerospace and Electronic Systems, IEEE Signal Processing Letters, IEEE Trans. Circuits and Systems, Scientific Reports He has also served as guest editors for the special issue “Intelligent Transportation Systems” for the International Journal on Information Fusion and “Cognitive Sensor Networks” for the IEEE Sensor Journal. He is the editor of the Springer book series on “Information Fusion and Data Science”. He is a Fellow of IEEE and SPIE.