Wei Cai

Wei Cai is a Professor of Mechanical Engineering at Stanford University with a courtesy appointment in Materials Science and Engineering. His research spans multiscale materials modeling, focusing on defect microstructures, atomistic simulation methods, machine learning applications, and metallurgical processes in metal 3D printing.

• Academic Background: PhD in Nuclear Engineering from MIT (2001)
• Current Role: Faculty in Mechanical Engineering, Stanford

Research Interests center on computational mechanics, dislocation dynamics, and stretchable electronics. Key areas include:

• Predicting mechanical strength across atomic to continuum scales
• Developing long timescale atomistic simulations
• Machine learning for materials property prediction
• Microstructure-property relationships in nanotube networks
• Metal additive manufacturing process modeling

Recent Publications (2023-2025) demonstrate expertise in dislocation mechanics, dual-phase alloys, self-healing polymers, and machine learning-enhanced materials simulations, with applications spanning titanium-oxygen alloys, perovskite phase separation, and nanowire fabrication.

Awards include:

• Presidential Early Career Award (2004)
• NSF Career Award (2006)
• AFOSR Young Investigator (2006)
• ASME Hughes Young Investigator (2013)
• Dislocations 2016 Scientific Achievement Award

Teaching covers advanced topics in statistical mechanics and computational methods. He advises multiple doctoral and master's students in materials research.