Jie Chen

Jie Chen is an Assistant Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering. Their research bridges machine learning with engineering analysis and design under uncertainty, focusing on process-structure-property-performance relationships.

• PhD, Mechanical Engineering (2022) – Arizona State University
• MS, Civil Engineering (2018) – Beihang University
• BS, Civil Engineering (2015) – Beihang University

Research interests include: physics-informed machine learning, uncertainty quantification, predictive maintenance, materials design, and advanced manufacturing. The SEAD Lab develops methods to integrate engineering analysis into stochastic machine learning algorithms and uses AI for knowledge discovery in uncertain environments.

Recent publications emphasize:

• Digital twin frameworks combining machine learning and Bayesian optimization
• Graph neural networks for high-entropy alloy and molecular mixture property prediction
• Physics-guided neural networks for fatigue life analysis of additively manufactured alloys
• Uncertainty quantification in imbalanced regression tasks and multi-fidelity data fusion
• Real-time imaging of polymer deformation mechanisms

The lab actively mentors students, including PhD candidate Yisheng Lu, and manages projects in predictive maintenance, fatigue modeling, and materials design.