Page 4 — Guangshuai Han

Guangshuai(Jerry) Han

Guangshuai Han leverages artificial intelligence to drive transformative research across materials and device design. More broadly, he is committed to developing AI-for-science approaches that accelerate innovation across disciplines.

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.

He is currently a Postdoctoral Associate at Johns Hopkins University, where his research focuses on applying AI to tackle the extreme complexity of disordered materials systems. Through these approaches, he aims to open new directions for high-entropy disordered materials design and discovery.

Email
Google Scholar
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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