Dong Chen

Dong Chen is a Visiting Assistant Professor in the Department of Mathematics at Michigan State University, located in C331 Wells Hall. His research focuses on integrating topological methods with machine learning to address challenges in materials science, computational chemistry, and drug discovery. He specializes in applying algebraic topology, persistent homology, and graph theory to analyze molecular structures, predict material properties, and model complex biological systems.

His research interests include:

• Topological data analysis for materials discovery
• Multiscale modeling of energy systems
• Artificial intelligence in anti-addiction drug development
• Machine learning for protein-ligand interactions

Recent work emphasizes leveraging topological features to enhance predictive models in areas like superionic conductors, drug resistance prediction, and carborane stability analysis. His contributions bridge abstract mathematical concepts with practical applications in chemistry and biology.

No academic awards or grants are explicitly listed in the provided information. He currently advises no documented students, though his work involves collaborations with interdisciplinary teams.