Speak: Prof. Cyrus Chan
Time: 16:00-17:30, Dec. 5
Host: Prof. Jie Zheng
Abstract:
AI successes, like Deep learning on IMAGENET and AlphaGO on playing go, have generated great hype and hope on revolution with AI. With recent buzz stories of fancy AI applications, come also the AI landing challenges in traditional industries. In this talk, I will share the challenges of AI landing with a realistic industrial setting in the pharmaceutical domain, and what endeavors we are making to overcome these challenges. By applying cutting-edge and industry-ready deep learning models and AI power-grid (e.g. Transformer for translation, AI platform for summarization, text classification tasks), we further develop practically innovative tools and processes that maximize AI-human synergy to close the gap of AI landing, to improve efficiency and predictability in practice.
Bio:
Dr. Cyrus Chan is the Executive Director of Big Data and Artificial Intelligence Unit, WuXi AppTec. The new department closely works with Business and Operation Units to design, develop, and execute major AI programs & projects.
Prior to joining WuXi AppTec in 2018, Cyrus was Principal Scientist at Philips Research China AI Lab, and a project team CEO in Philips’ Breakthrough Acceleration Program. Before that, he worked on genomics in a member lab of ENCODE consortium at UCLA. He used to work at the Chinese University of Hong Kong (CUHK) as a visiting assistant professor. Cyrus has hands-on experience in the field of machine learning, AI algorithms and applications, visual analytics, biomedical informatics and technology transfers. He has about 40 international publications (e.g. ACM/IEEE Transactions, Bioinformatics, Nuclear Acids Research, Genome Research) in related areas, and filed over 20 international patent applications in healthcare AI.
Cyrus graduated from CUHK and obtained his Ph.D. in computer science & engineering. He got his B.S. degree in computer science from Fudan University.
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