Dylan Anstine

Contact Information

Address: Engineering Bldg.
428 S Shaw Ln
Room: 1248
East Lansing , MI 48824

Phone:

(517) 432-1575

Email:

anstined@msu.edu

Assistant Professor

Chemical Engineering and Materials Science

Biography

Dylan Anstine is an Assistant Professor in the Department of Chemical Engineering and Materials Science at Michigan State University. His current research interests focus on several areas at the interface of artificial intelligence and chemical science, including machine learned interatomic potentials, machine-human interfaces for chemical discovery, artificial intelligence in computer aided synthesis planning, and microporous materials for carbon capture. Prior to joining MSU, he earned his Ph.D. in materials science and engineering at the University of Florida, which was followed by a postdoctoral research fellowship at Carnegie Mellon University.

Education

  • Postdoctoral Research Fellow, Carnegie Mellon University (2021-2025)
  • Ph.D., Materials Science and Engineering, University of Florida, 2021

Research Interests

  • Machine-Learned Interatomic Potentials
  • Machine-Human Interfaces for Chemical Discovery
  • Artificial Intelligence for Computer-Aided Synthesis Planning
  • Microporous Materials for Carbon Capture

Research Lab

The Anstine Research Lab

Selected Publications

  1. Anstine, D. M., Zhao, Q., Zubatyuk, R., Zhang, S., Singla, V., Nikitin, F., Savoie, B. M., Isayev, O., AIMNet2-rxn: A Machine Learned Potential for Generalized Reaction Modeling on a Millions-of-Pathways Scale, preprint, https://doi.org/10.26434/chemrxiv-2025-hpdmg
  2. Rapp, J., Anstine, D. M., Gusev, F., Nikitin, F., Yun, K., Borden, M., Bhat, V., Isayev, O., Leibfarth, F., Design of Tough 3D Printable Elastomers with Human-in-the-Loop Reinforcement Learning, Angewandte Chemie, e202513147 https://doi.org/10.1002/ange.202513147
  3. Anstine, D. M., Zubatyuk, R., Gallegos, L., Paton, R., Weist, O., Nebgen B., Jones, T., Gomes, G., Tretiak, S., Isayev, O., Transferable Machine Learning Interatomic Potential for Pd-Catalyzed Cross-Coupling Reactions, preprint, https://doi.org/10.26434/chemrxiv-2025-n36r6
  4. Anstine, D. M., and Isayev, O., Generative Models as an Emerging Paradigm in the Chemical Sciences, J. Am. Chem. Soc., 2023, 145(16), 8736-8750. https://doi.org/10.1021/jacs.2c13467
  5. Anstine, D. M., and Isayev, O., Machine Learning Interatomic Potentials and Long-Range Physics, J. Phys. Chem. A, 2023, 127(11), 2417-2431. https://doi.org/10.1021/acs.jpca.2c06778

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