Dr. Surdeanu earned a Ph.D. in Computer Science from Southern Methodist University, Dallas, Texas, in 2001. He has more than 15 years of experience in building systems driven by natural language processing (NLP) and machine learning. His experience spans both academia (Stanford University, University of Arizona) and industry (Yahoo! Research and two NLP-centric startups). During his career he published more than 80 peer-reviewed articles, including two articles that were among the top three most cited articles at two different NLP conferences. He was a leader or member of teams that ranked in the top three at seven highly competitive international evaluations of end-user NLP systems such as question answering and information extraction. His work was funded by several government organizations (DARPA, NIH), as well as private foundations (the Allen Institute for Artificial Intelligence, the Bill & Melinda Gates Foundation).
Dr. Surdeanu's current work focuses on using machine reading to extract structure from free text, and using this structure to construct causal models that can be used to understand, explain, and predict hypotheses for precision medicine.