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Artificial Intelligence (AI) has demonstrated unparalleled potential across industries and daily lives. In particular, AI for Science has emerged as a powerful tool for addressing complex scientific challenges by designing new AI methods. Its success in various fields such as physics, biology, drug design, and weather forecasting has garnered significant attention. This talk aims to provide an overview of the current opportunities and challenges in AI for Science. Additionally, it will offer a concise introduction to our recent research endeavors on developing AI methods for material science, biology, and weather forecasting.
Wanli Ouyang received his PhD degree from the Department of Electronic Engineering, The Chinese University of Hong Kong. He is now a professor at Shanghai AI Lab and The Chinese University of Hong Kong. His research interests include pattern recognition, machine learning, and AI for Science. Before that, he was an associate professor at The University of Sydney. He led the team ranking first in the 2015 and 2016 ImageNet ILSVRC Challenge. He was awarded IEEE TCSVT best paper award. He served as the associate editor of TPAMI, IJCV and PR, and the Senior Area Chair of CVPR and NeurIPS.
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