A Science Apprentice for Biophysics

Data Scientist in Gilead Sciences


333 Lakeside Dr

Foster City, CA, 94404

I am excited to introduce myself as a Data Scientist at Gilead Sciences, specializing in the deployment of state-of-the-art machine learning models to revolutionize clinical trial design and drug discovery processes. With a solid foundation in data science and a deep commitment to enhancing healthcare outcomes, I am fully dedicated to advancing Gilead’s mission of pushing the boundaries of medical research and delivering innovative solutions to patients worldwide.

My educational journey includes completing a Bachelor’s degree in Biosciences from Zhejiang University in 2017. Subsequently, I pursued a Ph.D. in Computational Biology and earned a master’s degree in Computer Science from Rice University in 2023. My research interests encompass a broad spectrum of areas, including protein folding, molecular dynamics, deep learning, and various computational biology challenges.

Beyond the research, I like playing the piano, badminton, diving, plant identification, and traveling.

Latest news

Feb 18, 2023 I am honored to be the recipient of Student Award in Physical Cell Biology in 2023 BPS Annual meeting!
Jul 31, 2022 This is the first day that I set up a personal website. :sparkles: :smile:

Selected publications

  1. NAR
    AWSEM-Suite: a protein structure prediction server based on template-guided, coevolutionary-enhanced optimized folding landscapes
    Shikai Jin, Vinicius G Contessoto, Mingchen Chen, Nicholas P Schafer, Wei Lu, Xun Chen, Carlos Bueno, Arya Hajitaheri, Brian J Sirovetz, Aram Davtyan, and others
    Nucleic Acids Research 2020
  2. JCTC
    Protein structure prediction in CASP13 using AWSEM-Suite
    Shikai Jin*, Mingchen Chen*, Xun Chen*, Carlos Bueno, Wei Lu, Nicholas P Schafer, Xingcheng Lin, José N Onuchic, and Peter G Wolynes
    Journal of Chemical Theory and Computation 2020
  3. PNAS
    Computationally exploring the mechanism of bacteriophage T7 gp4 helicase translocating along ssDNA
    Shikai Jin, Carlos Bueno, Wei Lu, Qian Wang, Mingchen Chen, Xun Chen, Peter G Wolynes, and Yang Gao
    Proceedings of the National Academy of Sciences 2022
  4. IUCrJ
    A deep learning solution for crystallographic structure determination
    Tom Pan*,  Shikai Jin*, Mitchell D Miller*, Anastasios Kyrillidis, and George N Phillips
    IUCrJ 2023