Fan Yang

Dr. Fan Yang is an Assistant Professor in the Department of Computer Science at Wake Forest University. He received his Ph.D. in Computer Science from Rice University, under the supervision of Dr. Xia (Ben) Hu.

Besides, in industries, he worked or interned with J.P. Morgan AI Research, Visa Research and Meta AI.His research interests generally lie in the areas of Data Mining and Machine Learning. More specifically, He focuses on the broad range of topics related to Trustworthy AI, with particular emphasis on Interpretable Learning and Model Explainability. His overall research goal is to make AI auditable, comprehensible, ethical, fair, responsible, robust, safe and verifiable. Dr. Yang also interested in Trustworthy AI downstream applications, including (but not limited to) Misinformation Detection, Recommender System, Health Informatics and Financial Forecasting, as well as its correlative intersections with Computer Vision (CV), Natural Language Processing (NLP) and Human-Computer Interaction (HCI).

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Teaching

Classes taught:

• CSC 112 – Fundamentals of Computer Science
• CSC 374/674 – Machine Learning

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Publications

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Research

• Post-Hoc Interpretation Techniques: Feature attribution, Counterfactual explanation; 
• Knowledge-Aware Interpretable Learning: Knowledge integration, Interactive learning; 
• Intrinsic Interpretability Design: Graphical modeling, Symbolic learning; 
• Human-Friendly Interpretation: Semantic concepts, Natural language; 
• Trustworthy AI Applications: Cancer diagnosis, Environmental science.