William Wang

William Wang

Mellichamp Chair in Artificial Intelligence and Designs
​Computer Science


Computer Science


2005 Henley Hall

University of California, Santa Barbara
Santa Barbara, CA 93106


Early CAREER Award, National Science Foundation; Karen Sparck Jones Award, British Computing Society; Undergraduate Research Faculty Mentoring Award, Computing Research Association; Young Faculty Award, U.S. Defense Advanced Research Projects Agency (DARPA); Faculty Research Award, JP Morgan Chase; AI's 10 to Watch of 2020, IEEE Intelligent System; IBM Faculty Award; Facebook Research Award; Adobe Research Award; Inaugural Notable Data Set Award


Programming Languages and Software Engineering

Wang is the director of UC Santa Barbara's Center for Responsible Machine Learning. He studies the theoretical foundation and practical algorithms for Artificial Intelligence. To build intelligent machines that can tackle challenging reasoning problems under uncertainty, he has pursued answers via studies of Machine Learning, Natural Language Processing, and Interdisciplinary Data Science. More specifically, he is interested in designing scalable inference and learning algorithms to analyze massive datasets with complex structures. In particular, he advances methods in the following research areas: Statistical Relational Learning, Knowledge Representation and Reasoning, Natural Language Processing, Speech, and Computational Social Science. Currently, he is nterested in advancing challenging problems in Artificial Intelligence, such as Natural Language Understanding, Information Extraction, and Learning to Reason. 


PhD ​ Computer Science, Carnegie Mellon University
MS  Columbia University