Chenguang Wang

Chenguang Wang is an Assistant Professor in the Department of Computer Science & Engineering at Washington University in St. Louis. He is affiliated with the McKelvey School of Engineering and the Division of Computational & Data Sciences. His research focuses on natural language processing (NLP), machine learning, and their applications in science, biomedicine, mathematics, economics, and blockchain.

• Education:
• Postdoc, University of California, Berkeley (2022)
• PhD, Peking University (2016)
• BS, Beijing Institute of Technology (2011)

His expertise includes developing NLP techniques, deep learning models, knowledge graphs, and open-source systems like AutoGluon and GluonNLP. He has held positions at Amazon AI and IBM Research-Almaden. Notably, he received honorable mention for the 2016 ACM China Doctoral Dissertation Award. His current research emphasizes improving large language models' grounding, consistency, and trustworthiness, supported by grants such as the 2023 Here & Next Seed Grant.

Chenguang leads research on neural symbolic models, code understanding/generation, and responsible AI (security, robustness, interpretability, fairness). His work bridges theoretical advancements with practical applications across interdisciplinary domains.