Tianshu Feng

Tianshu Feng is an Assistant Professor in the Department of Systems Engineering and Operations Research at George Mason University's College of Engineering and Computing. His research focuses on data-driven approaches in machine learning, statistical modeling, and explainable AI, with applications in healthcare, finance, transportation, and bioinformatics.

• PhD in Industrial Engineering, University of Washington
• BS in Statistics, University of Science and Technology of China

His work emphasizes developing flexible and robust models through interdisciplinary collaboration. Key research areas include model fairness, active learning, and data exploration. Recent projects include predicting drug responses using neural networks and improving credit decision transparency via Shapley decomposition.

His publications span topics like federated learning privacy, zero-inflated transportation models, and gene-environment interactions in diabetes research. He previously worked as a Quantitative Analytics Specialist at Wells Fargo before joining academia.