Research
Scientific background & publications
Scientific training and publications supporting an industry career in applied data science, forecasting, and optimization.
My research background is in computational modeling of complex systems. During my Ph.D. at Kyoto University, I developed particle-based models to study collective cell dynamics and the behavior of thousands of interacting agents.
That work shapes how I approach applied data science: make assumptions explicit, connect local behavior to system-level outcomes, and validate a model before using it to inform a decision.
Research illustration
Selected publications
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J. Li, S. Schnyder, M. Turner, and R. Yamamoto (2022). Competition between Cell Types under Cell Cycle Regulation with Apoptosis. Physical Review Research, 4, 033156.
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J. Li, S. Schnyder, M. Turner, and R. Yamamoto (2021). Role of the Cell Cycle in Collective Cell Dynamics. Physical Review X, 11, 031025. (Highlighted by Kyoto University)
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J. Wang, J. Li, W. Cao, L. Zhu, and R. Lakerveld (2020). An ion-specific electrolyte non-random two-liquid segment activity coefficient model with improved predictive capabilities for aqueous electrolyte solutions. Fluid Phase Equilibria, 517, 112605.
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J. Li (2016). Comparison of Energy Consumption between Propane–Propene Distillation Separation Process and Prospect Forecast. Natural Gas and Oil, 34(6), 46–50.
Selected talks
- March 2022 — APS March Meeting. Competition between Cell Types under Cell Cycle Regulation with Apoptosis.
- February 2022 — Warwick Physics Department Seminar. The Role of the Cell Cycle in Collective Cell Dynamics.
- January 2022 — Active Matter Workshop, Meiji University. Competition between Cell Types under Cell Cycle Regulation with Apoptosis.