EducationPostdoc, University of California, Berkeley, 2022
PhD, Peking University, 2016
BS, Beijing Institute of Technology, 2011
Develops natural language processing techniques and systems
Chenguang Wang has broad interests in natural language processing and machine learning. His work focuses on fundamental NLP research including deep learning models, language models, structure prediction, knowledge graphs, language representation and generation, language and vision, responsible models (security, robustness, interpretability, fairness), neural symbolic models, code understanding and generation, as well as applications of NLP for science, biomedicine, math, economics, and blockchain. He has created several open-source deep learning systems, including AutoGluon and GluonNLP.
BiographyChenguang Wang joined Washington University in St. Louis in 2022. Before that, he was a postdoc in Computer Science at UC Berkeley. He was previously a research scientist at Amazon AI and a research staff member at IBM Research-Almaden. He was nominated for the 2016 ACM China Doctoral Dissertation Award and received honorable mention (one of the two national finalists).