Tenure Track Assistant Professor of Chemical Engineering

PKU → Notre Dame → MIT → BU → UToledo

(starting at UToledo in August 2026)
"Never miss an opportunity to be fabulous "

Biography

I will join the Department of Chemical Engineering at the University of Toledo as a tenure-track Assistant Professor in August 2026. My independent research group develops physics-informed AI methods, including generative models, language models, AI for science foundation models, and graph learning, to understand, design, and engineer complex polymers, soft materials, macromolecules, biomacromolecular systems, and molecular interfaces. I am particularly interested in developing physics-informed AI models into applications of polymers and biomacromolecules in healthcare, sustainability, energy, and gas separation.

Before joining UToledo, I was a Postdoctoral Associate at the Department of Chemistry, Boston University, working with Prof. Qiang Cui from 2025 to 2026, and a Postdoctoral Associate at the Department of Chemical Engineering, Massachusetts Institute of Technology (MIT), working with Prof. Bradley D. Olsen and Dr. Debra J. Audus from 2022 to 2025.

I received my Ph.D. from the University of Notre Dame in 2022, working with Prof. Jonathan K. Whitmer, and my B.S. from Peking University in 2017, where I completed my undergraduate thesis with Prof. Hong Jiang.

My group at the University of Toledo is recruiting motivated students and postdoctoral researchers interested in physics-informed AI, generative models, language models, AI for science foundation models, graph learning, complex polymers, soft materials, and biomacromolecular systems.

Awards & Honors

  • 2023. ACS Polymeric Materials Science and Engineering (PMSE) Future Faculty Scholar.
  • 2023. NIST Postdoctoral & Early-career Association of Researchers (PEAR) Accolades Outstanding Technical Finalist.
  • 2023. Big Data Award at ACS Fall 2023 Big Data in Polymer Chemistry session.
  • 2023. Selected Attendees of ACS Postdoc to Faculty Workshop.
  • 2023. Selected Attendees of Soft Matter Future Faculty Workshop.
  • 2023. Winner, MIT ChemE Teach-Off 2023 Competition.
  • 2023. Forum for Early Career Scientists (FECS) Travel Grant, APS March 2023 Meeting.
  • 2020. Graduate School Professional Development Award, University of Notre Dame.
  • 2020. Graduate Student Union Conference Presentation Grant, University of Notre Dame.
  • 2020. DSOFT Travel Grant, APS March 2020 Meeting.
  • 2020. Outstanding Paper Award, Department of Chemical and Biomolecular Engineering, University of Notre Dame.
  • 2019. Graduate School Professional Development Award, University of Notre Dame.
  • 2019. Graduate Student Union Conference Presentation Grant, University of Notre Dame.
  • 2019. Best Poster Award, 6th Annual Notre Dame-Purdue Soft Matter & Polymers Symposium.
  • 2016. Cryrus Tang CaringHeart Scholarship, Peking University.
  • 2015. Cryrus Tang CaringHeart Scholarship, Peking University.
  • 2014. Cryrus Tang CaringHeart Scholarship, Peking University.
  • 2014. National Endeavor Fellowship, Peking University.
  • 2013. Cryrus Tang CaringHeart Scholarship, Peking University.
  • 2012. 2nd Prize in the China National Olympic Chemistry Competition.

Publications

[Google Scholar]

    Published and Accepted Papers

    Published and accepted papers are shown newest first with monotonically decreasing numbering, while the earliest paper remains number 1. * indicates equal contribution.

    1. Meysam Mohammadi-Zerankeshi, Dylan J. Charland, Keira A. Donnelly, Geoffrey T. Nash, Jiale Shi, ..., Qiang Cui, Keith P. Johnston, Daniel A. Estabrook, Alexander E. Marras. Storage Buffer Composition Impacts Internal Structure, Freeze-Thaw Stability, and Transfection Efficiency of mRNA-Lipid Nanoparticles. ACS Nano Published online June 12, 2026. [Publisher]
    2. Jiale Shi, Zhongyi Wan, Renjie Zhu, Qiang Cui. Measuring Differences in Protein Allosteric Graphs Constructed via Molecular Dynamics Simulations. J. Chem. Theory Comput. Published online June 4, 2026. [Publisher] [Preprint] [PDF]
    3. Jiale Shi, Runzhong Wang, Nathan J. Rebello, Jiarui Lu, Debra J. Audus, Bradley D. Olsen. MacroSimGNN: Efficient and Accurate Calculation of Macromolecule Pairwise Similarity via Graph Neural Network. Macromolecules 2026, 59, 4, 1885-1900. [Publisher] [Preprint] [PDF] [Code]
    4. Joren Van Herck, ..., Jiale Shi, ..., Jonathan K. Whitmer, ..., Berend Smit. Assessment of Fine-Tuned Large Language Models for Real-World Chemistry and Material Science Applications. Chemical Science 2025, 16, 670-684. [Publisher]
    5. Qianxiang Ai, Fanwang Meng, Jiale Shi, Brenden Pelkie, Connor W. Coley. Extracting Structured Data from Organic Synthesis Procedures Using a Fine-Tuned Large Language Model. Digital Discovery 2024, 3, 1822-1831. [Publisher]
    6. Nathan J. Rebello, Akash Arora, Hidenobu Mochigase, Tzyy-Shyang Lin, Jiale Shi, Debra J. Audus, Eric S. Muckley, Bradley D. Olsen. BCDB: The Block Copolymer Phase Behavior Database. Journal of Chemical Information and Modeling 2024, 64, 16, 6464-6476. [Publisher]
    7. Jiale Shi, Dylan Walsh, Nathan J. Rebello, Weizhong Zou, Michael E. Deagen, Katharina A. Fransen, Xian Gao, Bradley D. Olsen, Debra J. Audus. Calculating Pairwise Similarity of Polymer Ensemble via Earth Mover's Distance. ACS Polymers Au. 2024, 4, 1, 66-76. [Publisher] [PDF] [Code]
    8. Kevin Maik Jablonka, ..., Jiale Shi, ... 14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon. Digital Discovery 2023, 2, 1233-1250. [Publisher]
    9. Jiale Shi, Nathan J. Rebello, Dylan Walsh, Weizhong Zou, Michael Deagen, Bruno Salomao Leao, Debra J. Audus, Bradley D. Olsen. Quantifying Pairwise Similarity for Complex Polymers. Macromolecules. 2023, 56, 18, 7344-7357. [Publisher] [PDF] [Code]
    10. Jiale Shi, Fahed Albreiki, Yamil J. Colon, Samanvaya Srivastava, Jonathan K. Whitmer. Using Transfer Learning to Leverage Prior Knowledge in the Prediction of Adhesive Free Energies between Polymers and Surfaces. J. Chem. Theory Comput. 2023, 19, 14, 4631-4640. [Publisher] [PDF] [Code]
    11. Jiale Shi, Michael J. Quevillon, Pedro H. Amorim Valenca, Jonathan K. Whitmer. Predicting Adhesion Free Energies of Polymer-Surface Interactions with Machine Learning. ACS Appl. Mater. Interfaces 2022, 14, 32, 37161-37169. [Publisher] [PDF] [Code]
    12. Jiale Shi, Shanghui Huang, Francois Gygi, Jonathan K. Whitmer. Free-Energy Landscape and Isomerization Rates of Au4 Clusters at Finite Temperatures. J. Phys. Chem. A 2022, 126, 21, 3392-3400. [Publisher] [PDF] [Code]
    13. Jiale Shi*, Hythem Sidky*, Jonathan K. Whitmer. Automated determination of n-cyanobiphenyl and n-cyanobiphenyl binary mixtures elastic constants in the nematic phase from molecular simulation. Mol. Syst. Des. Eng. 2020, 5, 1131-1136. [Publisher] [PDF] [Code] (* indicates equal contribution and co-first authorship)
    14. Jiale Shi, Hythem Sidky, Jonathan K. Whitmer. Novel elastic response in twist-bend nematic models. Soft Matter 2019, 15(41), 8219-8226. [Publisher] [PDF] (inside front cover)