Prof. Dipti Srinivasan
(Keynote Speaker)
IEEE Fellow
National University of Singapore, Singapore

Biography: Dipti Srinivasan is a Professor in the Dept. of Electrical & Computer Engineering, where she also heads the Centre for Green Energy Management & Smart Grid (GEMS). She is a Fellow of IEEE, and was awarded the IEEE PES Outstanding Engineer award in 2010. She is currently serving as an Associate Editor of IEEE Transactions on Sustainable Energy, IEEE Transactions on Smart Grid, IEEE Transactions on Evolutionary Computation, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Computational Intelligence magazine.

Prof. Frank Park
(Keynote Speaker)
IEEE Fellow
Seoul National University, South Korea

Biography: Prof. Frank Chongwoo Park received his BS in Electrical Engineering from the Massachusetts Institute of Technology in 1985, followed by his PhD in Applied Mathematics from Harvard University in 1991. From 1991 to 1995, he was an Assistant Professor of Mechanical and Aerospace Engineering at the University of California at Irvine. Since 1995 he has been the Professor of Mechanical and Aerospace Engineering at Seoul National University.

Prof. Park's research interests are in robot mechanics, planning and control, vision and image processing, and related areas of applied mathematics. He has been an IEEE Robotics and Automation Society Distinguished Lecturer, and received best paper awards for his work on visual tracking and parallel robot design. Having served on the editorial boards of the Springer Handbook of Robotics, Springer Tracts in Advanced Robotics (STAR), Robotica, and the ASME Journal of Mechanisms and Robotics, Prof. Park has also held adjunct faculty positions at the NYU Courant Institute and the Interactive Computing Department at the Georgia Institute of Technology. He is a Fellow of the IEEE, the current editor-in-chief of the IEEE Transactions on Robotics, the developer of the EDX course Robot Mechanics and Control I, II. He is also a co-author of the book, "Modern Robotics: Mechanics, Planning and Control" published in 2017.

Prof. Ljiljana Trajkovic
(Keynote Speaker)
IEEE Fellow
Simon Fraser University, Canada

Keynote Lecture: Data Mining and Machine Learning for Complex Networks

Abstract: Collection and analysis of data from deployed networks is essential for understanding communication networks. Data mining and statistical analysis of network data have been employed to determine traffic loads, analyze patterns of users' behavior, predict future network traffic, and detect traffic anomalies. The Internet has historically been prone to failures and attacks that significantly degrade its performance, affect the Internet connectivity, and cause routing disconnections. Frequent cases of various cyber threats have been encountered over the years and, hence, detection of anomalous behavior is a topic of great interest in cybersecurity. In described case studies, traffic traces collected by various collection sites are used to classify network anomalies. Various anomaly and intrusion detection approaches based on machine learning have been employed to analyze collected data. Deep learning, broad learning, gradient boosted decision trees, and reservoir computing algorithms were used to develop models based on collected datasets that contain Internet worms, viruses, power outages, ransomware events, router misconfigurations, Internet Protocol hijacks, and infrastructure failures in times of conflict. The reported results indicate that while performance of machine learning models greatly depends on the used datasets, they are viable tools for detecting the Internet anomalies.

Biography: Ljiljana Trajkovic received the Dipl. Ing. degree from University of Pristina, Yugoslavia, the M.Sc. degrees in electrical engineering and computer engineering from Syracuse University, Syracuse, NY, and the Ph.D. degree in electrical engineering from University of California at Los Angeles. She is currently a professor in the School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada. Her research interests include communication networks and dynamical systems. Dr. Trajkovic served as IEEE Division X Delegate/Director, President of the IEEE Systems, Man, and Cybernetics Society, and President of the IEEE Circuits and Systems Society. She serves as Editor-in-Chief of the IEEE Transactions on Human-Machine Systems. She is a Distinguished Lecturer of the IEEE Systems, Man, and Cybernetics Society and was a Distinguished Lecturer of the IEEE Circuits and System Society. She is a Fellow of the IEEE.

Prof. Hatice Gunes
(Keynote Speaker)
University of Cambridge, UK

Keynote Lecture: TBA

Abstract: TBA

Biography: Prof. Gunes is an internationally recognized scholar in affective computing and robotics. She is a former President of the Association for the Advancement of Affective Computing (AAAC) and was a Faculty Fellow (2019-2021) of the Alan Turing Institute – UK’s national centre for data science and artificial intelligence. She was an Honoree for the Sony Women in Technology Award with Nature 2025 which celebrates inspirational women in technology who are poised to redefine the future of their fields.

Hatice Gunes obtained her PhD in computer science from the University of Technology Sydney (UTS) in Australia as an awardee of the Australian Government International Postgraduate Research Scholarship (IPRS) - a prestigious scholarship awarded on the basis of academic merit and research capacity. As a postdoctoral researcher at Imperial College London, she played a crucial role in the EU SEMAINE project, that created the world's first publicly available multimodal, fully autonomous, and real-time human-agent interaction system ( the SAL system). Attentive to user affect and nonverbal expressions, the project developed novel nonverbal audiovisual human behaviour analysis and multimodal agent behaviour synthesis capabilities, and won the Best Demo Award at IEEE ACII’09 and the Best Paper Award at IEEE FG’11. <Personal Webpage>

Prof. Takayuki Kanda
(Keynote Speaker)
Kyoto University, Japan

Keynote Lecture:Social Robots in Public Spaces

Abstract: Social robots are beginning to appear in public spaces such as shopping malls, yet deploying them in real environments remains challenging. In this talk, I present a series of field studies using our humanoid robot Robovie, focusing on how robots can interact effectively with people and acquire social acceptance. While robotic technologies continue to advance, our work highlights the importance of human-robot interaction, namely how to design robot behavior in synergy with technological progress. For instance, although modeling human interaction has enabled robots to provide services such as guidance and information, real-world deployments have revealed critical issues, including interaction failure, congestion, and robot abuse. These challenges have led us to a new research direction, "moral interaction," in which robots are designed as social peers that elicit respectful and prosocial behavior. I will introduce our recent studies on understanding and mitigating robot abuse, as well as on leveraging robots to create positive social influence through timely and context-aware interactions.

Biography: Takayuki Kanda is a professor in Informatics at Kyoto University, Japan. He is also a Visiting Group Leader at ATR Intelligent Robotics and Communication Laboratories, Kyoto, Japan. He received his B. Eng, M. Eng, and Ph. D. degrees in computer science from Kyoto University, Kyoto, Japan, in 1998, 2000, and 2003, respectively. He is one of the starting members of Communication Robots project at ATR. He has developed a communication robot, Robovie, and applied it in daily situations, such as peer-tutor at elementary school and a museum exhibit guide. His research interests include human-robot interaction, interactive humanoid robots, and field trials.

Prof. Ruxu Du
(Keynote Speaker)
Fellow of Canadian Academy of Engineering
The Zhongke Jianchi Biotechnology Co., Ltd, China

Biography: Prof. Ruxu Du was born in China in 1955. He received his Master’s degree from the South China University of Technology in 1983 and his Ph.D. degree from the University of Michigan in 1989. He has taught in the University of Windsor, in Windsor, Ontario, Canada (1991⎯1999), the University of Miami, in Coral Gables, Florida. USA (1999⎯2001), the Chinese University of Hong Kong in Hong Kong SAR (2001⎯2018), and the South China University of Technology (2018⎯2021). Prof. Du is the founding director of the Guangzhou Chinese Academy of Sciences Institute of Advanced Technology (2011⎯2016), the founding dean of S. M. Wu School of Intelligent Engineering, South China University of Technology, as well as the founding director of the Institute of Precision Engineering in the Chinese University of Hong Kong. Prof. Du’s areas of research include AI applications in medicine, precision engineering, design and manufacturing (metal forming, machining, plastic injection molding and etc.), as well as robotics and automation. He has published over 500 papers in various academic journals and international conferences. He is the associate editor / the members of editorial board of six international journals.

Prof. Yang Chai
(Keynote Speaker)
IEEE Fellow
The Hong Kong Polytechnic University,
Hong Kong, China

Keynote Lecture: Bioinspired in-sensor Computing for Artificial Vision

Abstract: The demand for accurate perception of the physical world leads to a dramatic increase in sensory nodes. However, the transmission of massive and unstructured sensory data from sensors to computing units poses great challenges in terms of power‐efficiency, transmission bandwidth, data storage, time latency, and security. To efficiently process massive sensory data, it is crucial to achieve data compression and structuring at the sensory terminals. In‐sensor computing integrates perception, memory, and processing functions within sensors, enabling sensory terminals to perform data compression and data structuring. In this talk, I will describe our team’s efforts towards bioinspired in-sensor computing for artificial vision. I will talk about the framework of the in-sensor computing and demonstrate a few vision sensors for different scenarios, including visual adaptation, motion perception, as well as event-driven vision sensors for spiking neural network.

Biography: Prof. Yang Chai is the Chair Professor of Semiconductor Physics of the Hong Kong Polytechnic University. He is an IEEE Distinguished Lecturer, an IEEE Fellow, an Optica Fellow, IOP Fellow, and AAIA Fellow. He is the Director of Research Institute for Artificial Intelligence of Things, the Director of Joint Research Center of Microelectronics, and the Associate Dean of Faculty of Science (Research) at the Hong Kong Polytechnic University. He is also the Chair of Semiconductor Nanotechnology Alliance, the Vice President of the Physical Society of Hong Kong, and an Associate Editor of ACS Nano. His current research interest mainly focuses on emerging electronic devices. He is also a receipt of the Falling Walls Science Breakthroughs in Engineering and Technology for his work on “Breaking the Wall of Efficient Sensory AI Systems”, the BOCHK Science and Technology Innovation Prize, The Croucher Senior Fellowship, The Ho Leung Ho Lee (HLHL) Foundation Science and Technology Innovation Award, and NSFC Distinguished Scholar.