Guangshuai(Jerry) Han
Guangshuai Han develops AI-driven systems that accelerate discovery in materials and device design, with a broader mission of advancing AI-for-science methodologies capable of transforming scientific innovation. His work spans agentic AI, LLM-based scientific reasoning, machine-learning force fields, and interpretable graph neural networks for understanding and designing complex materials systems.

During his PhD, one of his major achievements was pioneering an AI-assisted piezoelectric sensing system that transformed highway infrastructure monitoring. This technology was adopted as a new AASHTO standard, recognized by Time Magazine as one of the Best Inventions of 2023, and successfully transferred into practice as the core technology of a startup company.




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03 From Materials to Wearable Electronics


This direction bridges fundamental materials design with applications in wearable electronics. Starting from atomic-scale modeling to create high-performance materials, the work extends to developing novel sensing mechanisms and tailored signal processing algorithms. Together, these efforts enable next-generation wearable devices that combine material innovation with intelligent data interpretation.

Research Sponsors:
  • National Science Foundation (NSF)
  • Pfizer
  • Eli Lilly
  • Genentech
Github Page:
Flexible Device Signal Processing: Pad-U
Lammps Post Processing: Lammps_postproc

Publication:
G. Han, Z. Zeng, N. Lu, Y. Feng, “Enhancing Piezoelectricity of PVDF with Biocompatible Organic Dopants: From Atomic-Scale Insights to Advanced Wearable Devices”, Nano Energy, 144, 11383, 2025.
Y. Feng, J.H. Joo, G. Han, N. Lu. “The effects of Fe addition for enhanced thermoelectric performance in p-type CuAlO2”, Engineered Science, 22, 822, 2023. (Featured as cover page)
G. Han, Y. Su, Y. Feng, and N. Lu, “Approaches for Increasing the β-phase Concentration of Electrospun Polyvinylidene Fluoride (PVDF) Nanofibers” ES Materials and Manufacturing, 6, pp. 75-80, 2019.




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