CV
Shengli Jiang, PhD
Develops physics-informed machine learning and AI methods, integrated with molecular simulation, to design soft materials and chemical products for energy and sustainability.
Experience
Assistant Professor
Principal Investigator, Computational Materials and Product Design (CMPD) Laboratory. Tenure-track faculty developing physics-informed machine learning and AI methods for soft materials design.
- Physics-informed machine learning for polymer and materials design
- Molecular simulation and multiscale modeling
Postdoctoral Associate
Advisor: Professor Michael A. Webb. Integrate molecular simulation and machine learning to design polymers with tailored properties.
- Physics-informed machine learning for polymer design
- Structure-property relationship modeling in soft materials
Lecturer
Course: Machine Learning in Chemical Science and Engineering
Research Intern
Electricity price forecasting; large language models for quality note analysis
Givens Associate
Graph neural architecture search for molecular property prediction
Undergraduate Researcher
Design of organic cathodes for lithium-ion batteries
Education
PhD , Chemical Engineering
- Advisor: Professor Victor M. Zavala
- Focused on machine learning for sensor design, solvent systems, electrochemistry, and sustainability.
B.S. , Chemical Engineering
- Worked with Professor Zheng Chen on lithium-ion battery cathode design.
Professional Services
Reviewer
Reviewed for journals including Chemical Reviews, Chemical Science, npj Computational Materials, Environmental Science & Technology, Digital Discovery, Molecular Systems Design & Engineering, Computers & Chemical Engineering, and others. Also for conferences: American Control Conference, IEEE Conference on Decision and Control.
Member
Department DECI Committee Member
Member
Department DEI Committee Member
Awards
Givens Associate Fellowship
Fellowship for research in mathematics and computer science
Poster Award
Recognized for outstanding poster presentation
Travel Award
Support for conference attendance