About me

I am Yingce Xia, a researcher at the Zhongguancun Academy. Prior to this, I served as a Principal Research Manager at Microsoft Research, specializing in generative AI and AI for science. My research focuses on building foundation models for molecular science, with a particular emphasis on small molecule and protein design. I collaborate closely with leading biomedical organizations, such as GHDDI, and top pharmaceutical companies to translate AI innovations into real-world applications. I have authored over 70 publications in top journals and conferences, with more than 7,900 Google Scholar citations.

I am always open to new collaboration opportunities! Feel free to reach out to me via email at yingce.xia@gmail.com or yingce.xia@outlook.com

Current research focus

  • Developing foundation models for molecular science
  • Advancing AI applications in drug discovery
  • Exploring and improving large language models

Education

  • University of Science and Technology of China, Sep. 2013 to Jun. 2018
    • Ph.D in Electronic & Engineering ◊ Joint Ph.D Program with Microsoft Research Asia
    • Department of Information Science and Technology
    • Ph.D Supervisors: Prof. Tie-Yan Liu and Prof. Nenghai Yu.
  • University of Science and Technology of China, Sep. 2009 to Jun. 2013
    • B.S. in Information Security
    • Department of Information Science and Technology

Professional Activities

  • Action editor: TMLR
  • AC: ICML 2024 to 2025; NeurIPS 2023 to 2025
  • SPC member: AAAI 2020~2022, 2026; IJCAI 2021; AAMAS 2022
  • Reviewer: Nature Method; Nature Machine Intelligence
  • PC members: NeurIPS 2018 to 2022; ICML 2019 to 2023; ICLR 2019 to 2022; CVPR 2019 to 2021; ICCV 2019/2021; ECCV 2020; EMNLP 2020/2021

Teaching

  • Advanced machine learning, Chinese Academic of Sciences, 2023
    • Covered topics: Deep learning basics, meta learning, generative adversarial network, dual learning
  • Microsoft Advanced machine learning, Microsoft AI School China, 2021 and 2022
    • Covered topics: Meta learning & automatic machine learning, generative adversarial network, dual learning, natural language processing
  • Advanced machine learning, Tsinghua University, 2019 and 2021
    • Covered topics: Meta learning & automatic machine learning, generative adversarial network, dual learning, natural language processing
  • Dual learning, IJCAI, Macau, China, 2019

I will add more information when I am free.