Overview
Personal Profile
Jeff Law leads the development and application of machine learning models to design bio-based polymers for various applications, as well as to engineer enzymes to improve their stability with respect to temperature, pH, and organic solvents for better production of biofuels.
Research Interests
Machine learning
Enzyme engineering
Bio-based materials design
Molecular dynamics simulations
Professional Experience
Postdoctoral Researcher, NLR (2020–2023)
Education/Academic Qualification
Bachelor, Bioinformatics, Brigham Young University
PhD, Genetics, Bioinformatics, and Computational Biology, Virginia Tech
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Collaborations and Top Research Areas From the Past 5 Years
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Cracking the Code of Multi-Layer Films to Promote Circularity in Single-Use Plastic Packaging: Article No. 1489
Quinn, E., Hamernik, L., Law, J., Clarke, R., Milrod, M., Kozarekar, S., Mick, R., Sobkowicz, M., Broadbelt, L., Knott, B. & Knauer, K., 2026, In: Nature Communications. 17, 14 p.Research output: Contribution to journal › Article › peer-review
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PET-FBA: A Lightweight Enzyme Allocation and Thermodynamics-Constrained Flux Analysis Approach to Explore Escherichia Coli Metabolic Adaptation to Intracellular Acidification
Wu, C., Law, J., Onyenemezu, O., Roy, J., St. John, P., Jernigan, R., Bomble, Y. & Jarboe, L., 2026, In: Metabolic Engineering. 94, p. 202-212 11 p.Research output: Contribution to journal › Article › peer-review
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Charting the Chemical Space of Zintl Phases with Graph Neural Networks and Bonding Insights
Chaliha, R., Kothakonda, M., Lee, C.-W., Law, J., Yang, Q., Bobev, S. & Gorai, P., 2025, In: Journal of Materials Chemistry A. 13, 39, p. 33385-33396 12 p.Research output: Contribution to journal › Article › peer-review
1 Scopus Citations -
End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning
St. John, P., Biagioni, D., Tripp, C., Law, J., Skordilis, E., Duplyakin, D., Clark, S., Paton, R., Sowndarya S. V., S., Gorai, P., Pandey, S., Stevanovic, V., Bray, A., Daley, T. & Meissner, J., 2025, 17 p.Research output: NLR › Technical Report
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Plug & Play Directed Evolution of Proteins with Gradient-Based Discrete MCMC: Article No. 025014
Emami, P., Perreault, A., Law, J., Biagioni, D. & St. John, P., 2023, In: Machine Learning: Science and Technology. 4, 2, 21 p.Research output: Contribution to journal › Article › peer-review
16 Scopus Citations