Kerr Ding

kerrding at gatech.edu

I am a fifth-year CS Ph.D. candidate in the School of Computational Science and Engineering, Georgia Institute of Technology, where I am fortunate to be advised by Prof. Yunan Luo. Before this, I obtained my bachelor’s degree from Peking University. I was previously an AI Research Scientist Intern at Chan Zuckerberg Biohub in Summer 2026.

My research interests lie at the intersection of machine learning (ML) and computational biology. I am broadly interested in developing novel ML tools to accelerate biological research, with a particular focus on tackling protein-related challenges. My primary research focuses include:

  • Developing foundational models for protein engineering and protein design
  • Scalable and generalizable characterization of protein functions
  • Graph-based modeling of biological networks for disease target identification

News

Sep 04, 2026 Our work on Deconvolving mutation effects on protein stability and function has been accepted for a selected talk at the New England Computational Biology Symposium (NECB 2026), which will be held on October 1-2 in Cambridge, MA!
Feb 24, 2026 Our paper on Deconvolving mutation effects on protein stability and function has been accepted for presentation at RECOMB 2026, which will be held on May 26-29 in Thessaloniki, Greece!
Nov 24, 2025 I have been invited to present our methodology for variant effect prediction at CAGI7, which will be held December 6-8 in Boston, MA!
Feb 05, 2025 Our paper on ML-guided combinatorial library design in enzyme engineering has been selected for presentation in the Highlights Track at RECOMB 2025, occurring April 26-29 in Seoul, South Korea! I will also be presenting the proceeding paper Learning maximally spanning representations improves protein function annotation on behalf of my labmate Jiaqi Luo!
Jul 29, 2024 One paper on ML-guided combinatorial library design in enzyme engineering has been published in Nature Communications.
May 29, 2024 One paper on Conformal prediction for enzyme function has been published in 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!

Preprints

  1. bioRxiv
    Deconvolving mutation effects on protein stability and function with disentangled protein language models
    Kerr Ding, Ziang Li, Tony Tu, Jiaqi Luo, and Yunan Luo
    Extended journal version under review, 2026
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  2. bioRxiv
    SynFit: Synergistic Contrastive Learning for Multi-Objective Protein Fitness Prediction and Optimization
    Tony Tu, Wei Huang, Ziang Li, Kerr Ding, Yang Yang, and Yunan Luo
    bioRxiv, 2026
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  3. bioRxiv
    Advances in Protein Function Prediction from the Fifth CAFA Challenge
    M Clara De Paolis Kaluza, Rashika Ramola, Parnal Joshi, Damiano Piovesan, Walter Reade, Sandra Orchard, Maria J Martin, Alex Ignatchenko, Kaggle Competition Participants (including Kerr Ding), Burkhard Rost, Christine A Orengo, Marc Robinson-Rechavi, Dannie Durand, Steven E Brenner, Casey S Greene, Sean D Mooney, Iddo Friedberg, and Predrag Radivojac
    bioRxiv, 2026
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Publications (at Georgia Tech)

  1. RECOMB
    Deconvolving mutation effects on protein stability and function with disentangled protein language models
    Kerr Ding, Ziang Li, Tony Tu, Jiaqi Luo, and Yunan Luo
    International Conference on Research in Computational Molecular Biology (RECOMB), 2026
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  2. iScience
    Pareto-optimal sampling for multi-objective protein sequence design
    Jiaqi Luo, Kerr Ding, and Yunan Luo
    iScience, 2025
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  3. Nat Commun
    Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering
    Kerr Ding†, Michael Chin†, Yunlong Zhao†, Wei Huang, Binh Khanh Mai, Huanan Wang, Peng Liu, Yang Yang, and Yunan Luo
    Nature Communications, 2024 (Highlights Track at RECOMB 2025)
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  4. Nat Rev Electr Eng
    Opportunities and challenges of graph neural networks in electrical engineering
    Eli Chien, Mufei Li, Anthony Aportela, Kerr Ding, Shuyi Jia, Supriyo Maji, Zhongyuan Zhao, Javier Duarte, Victor Fung, Cong Hao, and others
    Nature Reviews Electrical Engineering, 2024
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  5. 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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  6. ISMB
    Supervised biological network alignment with graph neural networks
    Kerr Ding, Sheng Wang, and Yunan Luo
    Intelligent Systems For Molecular Biology (ISMB)/Bioinformatics, 2023
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Academic Services

Reviewer
  • Conferences: RECOMB (2024-2026), ISMB (2024-2026), ACM-BCB (2025-2026), Pacific Symposium on Biocomputing (2027)
  • Journals: Bioinformatics, Cell Discovery, Transactions on Machine Learning Research (TMLR), IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Computational Biology and Bioinformatics, NAR Genomics and Bioinformatics, PLOS One, npj Artificial Intelligence, BMC Genomics, Scientific Reports, Frontiers in Artificial Intelligence, International Journal of Data Science and Analytics, Network Modeling Analysis in Health Informatics and Bioinformatics
  • Workshops: KDD–AI4Sciences (2027, 2026); NeurIPS–GEM Bio (2026), AI4DD (2026); ICLR–FM4Science (2026), GEM (2026, 2025), AI4NA (2025), MLMP (2025); CVPR–MM4Mat (2025)

Teaching

  • TA for CSE7850/CX4803 Machine Learning in Computational Biology (Spring 2025)
  • Guest lecturer for CSE8803 Machine Learning with Graphs (Fall 2023, Fall 2025) and CS8001 OAS: AI for Science (Summer 2025)