[IAS 2023 Workshop] Call for Registration: Biological Data Science, AI & Medicine Workshop

Last updated on Jun 10, 2023 2 min read

Our upcoming workshop on Biological Data Science, AI & Medicine is happening in Hong Kong on June 14-16! Join us for insightful talks from experts worldwide on AI’s cutting-edge research and applications in life sciences and medicine.

Overview

The primary objective of the program is to assemble leading scientists in the fields of computational biology, biomedical data science, and AI-driven medicine research. These experts will be given a platform to showcase their latest breakthroughs and discoveries, with the aim of promoting the dissemination of information to other academic communities and encouraging interdisciplinary communication and collaboration. Additionally, the program places significant emphasis on facilitating interaction between local and international scientists, with the goal of stimulating productive collaborations between these experts.

The implementation of the IAS-focused BAM workshop is expected to yield significant benefits for both HKUST, Hong Kong’s scientific community, and the overall reputation of the region in the field. By bringing together top computational biology and AI experts from across the globe, the program will foster open and extensive discussion on current knowledge and future advancements in the field. Moreover, the program will facilitate the establishment of connections among researchers. It is expected that the conference will attract around 100 participants from not only HKUST but also other universities in Hong Kong, providing a unique opportunity for faculty and students in the region to engage with world-renowned experts.

For detail information, please refer to the official website: http://ias.ust.hk/events/202306bam/

Invited Speakers

  • Hao CHEN (HKUST)
  • Yike GUO (HKUST)
  • Dali HAN (Beijing Institute of Genomics, Chinese Academy of Sciences)
  • Zheng HU (Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences)
  • Yuanhua HUANG The University of Hong Kong
  • Ying JING (Greater Bay Area Institute of Precision Medicine)
  • Zhaoqi LIU (Beijing Institute of Genomics, Chinese Academy of Sciences)
  • Dohyun NAM (Samsung Medical Center)
  • Ho-Keung NG (The Chinese University of Hong Kong)
  • Raul RABADAN (Columbia University)
  • David J. H. SHIH (The University of Hong Kong)
  • Xin WANG (The Chinese University of Hong Kong)
  • Angela WU (HKUST)
  • Can YANG (HKUST)
  • Li-sheng ZHANG (HKUST)
  • Shaoting ZHANG (Shanghai Artificial Intelligence Laboratory)
  • Qian ZHAO (The Hong Kong Polytechnic University)

*Listed in alphabetical order of last name