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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GitHub Page
04 Other Collaborations


Beyond his core research areas, he is engaged in diverse collaborations that span 3D-printed sensor design, advanced concrete materials for 3D printing, computer vision for material inspection, AI-guided polymer design, and solid-state materials research. These efforts reflect a broad commitment to integrating artificial intelligence with emerging technologies across multiple domains.


Research Sponsors:
  • National Science Foundation (NSF)
  • Defense Advanced Research Projects Agency (DARPA)
Github Page:
EMI Signal Processing: Strength_sensing


Publication:
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)
R. Wang, X. Gao, J.i Zhang, G. Han, “Spatial Distribution of Steel Fibers and Air Bubbles in UHPC Cylinder Determined by X-ray CT Method”, Construction and Building Materials, 160, pp. 39-47, 2018.
R. Wang, X. Gao, H. Huang, G. Han, “Influence of Rheological Properties of Cement Mortar on Steel Fiber Distribution in UHPC”, Construction and Building Materials, 144, pp. 65-73, 2017.




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