Keynote Speaker 

Bio: 

Dr. Uichin Lee is a Professor in the School of Computing at the Korea Advanced Institute of Science and Technology (KAIST), leading the Interactive Computing Lab, whose mission is to study intelligent positive computing systems that can intervene in threats to human health and digital wellbeing. He received a Ph.D. degree in computer science from UCLA in 2008. He worked for Alcatel-Lucent Bell Labs as a member of the technical staff before joining KAIST in 2010. He has joint affiliations with the Department of Industrial and Systems Engineering, the Graduate School of Data Science at KAIST, and the KAIST Health Science Institute. In 2023, he was inducted as a member of the SIGCHI Academy, an honorary group of individuals who have made substantial contributions to the field of human-computer interaction (HCI). He served as a program committee member of the key HCI conferences and journals, such as ACM CHI, CSCW, and Ubicomp, and as an editor for PACM HCI (CSCW) and IMWUT (Ubicomp). He received the best paper awards at ACM CHI’16, AAAI ICWSM’13, IEEE CCGrid’11, and IEEE PerCom’07, and an impact award from IEEE IoT Form’19.   

Abstract: 

Digital wellbeing" refers to the constructive engagement with digital technologies, allowing individuals to work efficiently, enhance social connections, and maintain a balanced, healthy lifestyle devoid of negative side effects such as distractions and over-reliance. This keynote delves into recent data-driven studies that investigate user interactions and contextual data to offer a comprehensive understanding of digital wellbeing and its interplay with physical, mental, and social wellbeing. Furthermore, a series of recent digital wellbeing services are reviewed to provide insights into potential avenues for future research on intervention design. A critical examination reveals that user interface design has, to date, been heralding fluid interactions and has so far neglected mitigating such side effects, which motivates an alternative for increasing interaction friction or even blocking user interaction as a tool for self-binding. The keynote culminates in a call to action, urging research communities to further conduct data-driven studies on digital wellbeing and explore novel personalized, data-driven, intelligent interventions in our ever-evolving digital landscape. 

Bio: 

Dr. Henry Leung is a professor of Electrical and Computer Engineering at the University of Calgary, Canada. He was previously with the Department of National Defence (DND) of Canada as a defense scientist. He has over 300 journal papers and over 250 refereed conference papers in the areas of signal and image processing, data mining, information fusion, machine learning, IoT, and sensor networks. He also holds more than 15 patents. Dr. Leung is the editor of the Springer book series on “Information Fusion and Data Science”. He has been an associate editor of various journals such as the International Journal on Information Fusion, IEEE Trans. Aerospace and Electronic Systems, IEEE Signal Processing Letters, IEEE Circuits and Systems Magazine, IEICE Trans. on Nonlinear Theory and Applications. He is a Fellow of IEEE and SPIE.

Abstract: 

The recent trends in machine learning and edge intelligence require developing trustworthy AI that allows operators to interact with these smart systems and edge devices. In this talk, we present an uncertainty-aware AI framework that aims to improve the trustworthiness between humans and machines by providing uncertainty measure of AI outputs. We integrate Bayesian deep learning with sensing to quantify the uncertainty of the AI output such as objection detection and then assess when the human operators can trust the model outputs. Given specific data samples, display and interact with operators to diagnose challenges of the system. Through the feedback of labelling such data samples, we explore how the systems can be adapted to changing conditions and subsequently improve over time with limited human supervision. We will present some applications of this framework to several industrial problems such as autonomous driving and manufacturing, where AI models provide high accuracy and speed for automated processing in object detection and recognition.

Bio: 

Prof. KC Santosh, a highly accomplished AI expert, is the chair of the Department of Computer Science, University of South Dakota. He earned his PhD in Computer Science - Artificial Intelligence from INRIA Nancy Grand East Research Centre (France) and worked as a research fellow at the National Institutes of Health. With funding of over $1.3 million, including a $1 million grant from DEPSCOR (2023) for AI/ML capacity building at USD, he has authored 10 books and published over 240 peer-reviewed research articles. He is an associate editor of multiple prestigious journals such as IEEE Transactions on AI, Int. J of Machine Learning & Cybernetics, and Int. J of Pattern Recognition & Artificial Intelligence. To name a few, Prof. Santosh is the proud recipient of the Cutler Award for Teaching and Research Excellence (USD, 2021), the President's Research Excellence Award (USD, 2019) and the Ignite Award from the U.S. Department of Health & Human Services (HHS, 2014). As the founder of AI programs at USD, he has taken significant strides to increase enrollment in the graduate program, resulting in over 2,000% growth in just three years. His leadership has helped build multiple inter-disciplinary AI/Data Science related academic programs, including collaborations with Biology, Physics, Biomedical Engineering, Sustainability and Business Analytics departments. Prof. Santosh is highly motivated in academic leadership, and his contributions have established USD as a pioneer in AI programs within the state of SD. 

Bio:

Prof.Shiho Kim (Senior Member, IEEE) founded the PAV Research and Development Center supported by Incheon Metropolitan City and Soomvi Inc., in 2020. He has been directing the Seamless Transportation Laboratory, since 2011. He is currently a Professor with the School of Integrated Technology, Yonsei University, Seoul, South Korea. His research interests include the development of software and hardware technologies for autonomous vehicles and reinforcement learning for intelligent transportation systems. 

Abstract

The DeSci (Decentralized Science) movement is heralding a new platform for technical publication in the realm of Web 3.0, marking a significant transition in the submission, review, publication, and accessibility of scientific content. This shift is crucial in the current digital landscape, where Web 3.0, characterized by its decentralized networks and smart contract functionalities, presents novel approaches that could drastically alter the dynamics of scientific communication, diverging from the conventional centralized systems led by dominant publishers and academic institutions. However, despite its promising horizons, this movement confronts several obstacles, such as maintaining the caliber and honesty of decentralized publications and upholding the endurance of these innovative platforms. In my keynote address, I will explore and deliberate on essential themes including:

-          The Paradigm Shift in Academic Publishing

-          Copyright and Ownership in DeSci

-          The Role of Web 3.0 and Blockchain in DeSci

-          Challenges and Barriers to DeSci Adoption

-          Impact on the Future of Research and Innovation

-          DAO Governance Models in Decentralized Science

 Through these focal points, we will delve into the intricate tapestry of decentralized science, charting its challenges, opportunities, and conceivable influence on the future of journal publications.