This panel brings together the world’s leading experts in computer vision to discuss “Diffusion Models for Image and Video Tasks”. Speakers are leaders from the various visual intelligence fields, ranging from generative AI: image/video generation, compositional generation, generation for compression, generation for autonomous driving, generation for security, and more. As we all know, diffusion models have
emerged as a powerful tool in the field of machine learning, particularly for generating high-quality images and videos. This panel discussion brings together experts from academia and industry to explore the cutting-edge applications and future directions of diffusion models, including but not limited to, Recent breakthroughs in diffusion models, Challenges and opportunities in image and video generation,
Applications in creative industries, healthcare, and entertainment, and Ethical considerations and responsible use of AI.

Speakers:

Shaolei Ren
Ren is an Associate Professor of Electrical and Computer Engineering at the University of California, Riverside. His research broadly focuses on AI, energy, and public health. His work has generated broader societal impacts, shaping AI policies adopted by international organizations such as the United Nations, UNESCO, and WHO. Additionally, his research has driven industry innovations, including the development of the first real-time water footprint reporting tool for computing. He is a recipient of the NSF CAREER Award (2015) and several paper awards, including at ACM e-Energy (2024, 2016) and IEEE ICC (2016). He received his Ph.D. from the University of California, Los Angeles.

Sharon Hsiao
Dr. Sharon Hsiao is Assistant Professor & David Packard endowed junior fellow in the Department of Computer Science & Engineering at Santa Clara University. Prior to SCU, Dr. Hsiao was an assistant professor at Arizona State University and Columbia University, where she established several research projects and taught graduate & undergraduate level courses. Dr. Hsiao’s research focuses on educational technologies, computational modeling, visual analytics, and adaptive technology for personalized learning. Her research methodology involves AI and HCI approaches, applied data science and machine learning techniques in researching effective technology to help people learn. Dr. Hsiao actively involves in several international research communities, including Educational Data Mining (EDM), Learning Analytics & Knowledge (LAK), Artificial Intelligence in Education (AIED), and European Conference on Technology Enhanced Learning (EC-TEL). She serves as the Program Chair of 14th International Conference on Educational Data Mining, Organizing Chair of the 9th of International Conference on Learning Analytics & Knowledge, and several other leadership and editing positions. (https://webpages.scu.edu/ftp/ihsiao/)

Irina Raicu
Irina Raicu directs the Internet Ethics program at the Markkula Center for Applied Ethics. She is a certified information privacy professional, and her work addresses a wide variety of topics—from online privacy to social media’s impact on society, from the digital divide to the ethics of encryption, and the many ethical issues associated with artificial intelligence. Raicu was a member of the Partnership on AI’s first working group on Fair, Transparent, and Accountable AI, and she served as a member of the initial cohort of the city of San Jose’s privacy advisory task force. Together with other center staff, Raicu has worked with multiple companies in the process of developing their responsible tech/responsible AI policies and processes. Her writing has appeared in publications including The Atlantic, U.S.A. Today, Forbes, MarketWatch, Slate, the San Francisco Chronicle, and she is the primary contributor to the blog Internet Ethics: Views from Silicon Valley. (https://www.scu.edu/ethics/about-the-center/people/irina-raicu/)

Moderator:

Yuhong Liu
Yuhong Liu, Associate Professor at the Department of Computer Science and Engineering, Santa Clara University. Her research interests include responsible AI, trustworthy computing and cyber security of emerging applications, such as online social media, Internet-of-things and Blockchain. She has published over 100 papers on prestigious journals and peer reviewed conferences. She is currently serving as an Associate Editor of IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Transactions on Service Computing (TSC), Multimedia Tools and Applications (MTAP), APSIPA Transactions on Signal and Information Processing (TSIP), and a Youth EBM Editor of the Blockchain: Research and Applications Journal. She serves as an IEEE Computer Society Distinguished Visitor (2022-2024), and an APSIPA Distinguished Lecturer (2021-2022). She is the recipient of the 2019 Researcher of the Year Award at School of Engineering, Santa Clara University, the 2013 University of Rhode Island Graduate School Excellence in Doctoral Research Award, and the Best Paper award of the IEEE International Conference on Social Computing 2010 (acceptance rate 13%). (https://www.scu.edu/engineering/faculty/liu-yuhong/)

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