Shengfeng Yang

Shengfeng Yang is an Assistant Professor of Mechanical Engineering at Purdue University, leading the Advanced Computation and Artificial Intelligence (ACAI) Lab. His research focuses on integrating computational methods and AI to solve complex problems in materials science, particularly in energy storage, nanomaterials, and interfacial mechanics.

Research Interests:

• Scientific Machine Learning for material property prediction
• Reliability analysis for semiconductors
• Physical Intelligence and Robotics (e.g., Vision-Language-Action models)
• Advanced Energy Materials (e.g., Li-ion battery anodes)
• Interfaces in Materials (e.g., grain boundary dynamics)

Publication Trends: His recent work emphasizes generative machine learning for nanomaterials, atomistic simulations for semiconductor reliability, and first-principles calculations for nuclear material defects. Earlier studies include phase-field modeling, phonon transport, and interfacial phase transitions.

Labs and Teams: He directs the ACAI Lab, which develops AI-driven tools for materials innovation, including applications in dendritic growth simulation, grain boundary evolution, and battery technology.