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University of Alberta, Canada
Plenary Speaker
Li Cheng is a Professor in the Department of Electrical and Computer Engineering, University of Alberta, Canada. His research interests include computer vision, multi-modal data analytics, and applications. In particular, his recent interests include 3D reconstruction and animation of human and animal motions. He has published over 200 papers in peer-reviewed journals and conferences, including a nomination for Best Paper Award at CVPR 2021, the best publication venue in computer vision. More recent details can be found at his lab website, https://vision-and-learning-lab-ualberta.github.io/. He serves as an Associate Editor for IEEE Trans. Image Processing (2026-), IEEE Trans. Multimedia (2021-26), Pattern Recognition (2019-), among others.
The University of Texas at Austin , USA
Plenary Speaker
Matthew Lease is a Distinguished Member of the Association for Computing Machinery (ACM), a Senior Member of the Association for the Advancement of Artificial Intelligence (AAAI), and an Amazon Scholar. Lease co-directs the $20M NSF-Simons AI Institute for Cosmic Origins (CosmicAI) and is a faculty founder and leader of UT's Good Systems, an eight-year, $20M university-wide Grand Challenge aimed at designing responsible AI technologies. In 2023-2024, Lease was invited four times to address the Texas Legislature on responsible AI.Lease directs the UT Austin Laboratory for Artificial Intelligence and Human-Centered Computing (AI&HCC), where his team's research spans artificial intelligence (AI) modeling and human-computer interaction (HCI) design. The lab creates novel datasets, builds AI models, and evaluates both model performance and their impact on end-users. When automated AI falls short, they design human-in-the-loop approaches, leveraging AI model explanations and creative user interfaces. To promote fair AI, the lab focuses on better annotation techniques to avoid bias and develops modeling strategies to mitigate dataset biases. Their work tackles real-world problems as part of UT Austin's Good Systems Grand Challenge, with an ongoing emphasis on content moderation-exploring automated, human-in-the-loop, and human-safe practices to combat disinformation, hate speech, and online polarization.