University of California, Santa Barbara
Santa Barbara, CA 93106
DARPA Young Faculty Award; IBM Faculty Award; Facebook Research Award; Adobe Research Award; Inaugural Notable Data Set Award
Wang 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