Computational Materials Design • AI for Materials • High-Entropy Materials
Wei Chen
Associate Professor
Department of Materials Design and Innovation
University at Buffalo
My group develops data-driven and physics-based modeling approaches to understand and design complex materials systems. We combine atomistic modeling, thermodynamic modeling, machine learning, statistical mechanics, and materials informatics to accelerate materials discovery and connect processing, structure, properties, and performance.
Research Focus
Research Vision
Modern materials design requires methods that are both physically grounded and data-aware. Our work aims to create predictive, interpretable, and manufacturing-relevant models for complex materials, especially compositionally complex alloys and ceramics.
Current Directions
- High-entropy and multi-principal element materials
- Defect-informed phase stability and transformation pathways
- Materials informatics for accelerated discovery
- Computational design for additive manufacturing
- AI-assisted modeling of structure–property relationships
Selected Links
For publications and citation information, please visit myGoogle Scholar profile. For official university information, please visit myUB faculty profile.