Kerr Ding

kerrding at gatech.edu

I am a CS Ph.D. student in the School of Computational Science and Engineering, Georgia Institute of Technology, advised by Prof. Yunan Luo. Before that, I obtained my bachelor’s degree from Peking University.

I am broadly interested in machine learning (ML) and computational biology. I am devoted to developing novel machine learning tools to aid biological research, and I am particularly interested in utilizing machine learning tools to address complex protein-related challenges. My primary research focuses include:

  • Machine learning-guided protein engineering
  • Biological network alignment

News

Jul 29, 2024 One paper on ML-guided combinatorial library design in enzyme engineering has published at Nature Communications.
May 29, 2024 One paper on Conformal prediction for enzyme function has published at PLOS Computational Biology.
Apr 11, 2023 One paper on Supervised biological network alignment has been accepted for presentation at ISMB 2023, which will be held on July 23-27 in Lyon, France!

Publications (at Georgia Tech)

  1. Nat Commun
    Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering
    Kerr Ding, Michael Chin, Yunlong Zhao, and 6 more authors
    Nature Communications 2024
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  2. Nat Rev Electr Eng
    Opportunities and challenges of graph neural networks in electrical engineering
    Eli Chien, Mufei Li, Anthony Aportela, and 8 more authors
    Nature Reviews Electrical Engineering 2024
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  3. PLOS CB
    Leveraging conformal prediction to annotate enzyme function space with limited false positives
    Kerr Ding, Jiaqi Luo, and Yunan Luo
    PLOS Computational Biology 2024
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  4. ISMB
    Supervised biological network alignment with graph neural networks
    Kerr Ding, Sheng Wang, and Yunan Luo
    ISMB/Bioinformatics 2023
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