Regina Barzilay is a computational linguist developing machine learning methods that enable computers to interpret unstructured document content and perform real-world tasks with the promise for significant societal impact.

Barzilay has made significant contributions to a wide range of problems in computational linguistics, including both interpretation and generation of human language. Much of her work is focused on designing machine learning models that do not require large amounts of annotations for training since such resources are not available for most languages and tasks. In the multilingual context, Barzilay created algorithms that leverage annotations from high-resource languages (i.e., such as English) to analyze languages that lack such annotations; this includes the vast majority of world languages.

Jointly with her students, Barzilay also pioneered the development of reinforcement learning methods for language grounding—that is, mapping language to entities and actions in the world.

Currently, Barzilay is focused on bringing the power of machine learning to oncology. In collaboration with physicians and her students, she is devising deep learning models that utilize imaging, free text, and structured data to identify trends that affect early diagnosis, treatment, and disease prevention.

Barzilay received B.A. (1993) and M.S. (1998) degrees from Ben-Gurion University of the Negev and a Ph.D. (2003) from Columbia University. She has been affiliated with the Massachusetts Institute of Technology since 2003 and is currently Delta Electronics Professor of Electrical Engineering and Computer Science. In 2017, Barzilay was named a MacArthur 'Genius Grant' Fellow.

Computers, Computer Science, Engineers, Linguistics, Science, Science & Technology, Tech Teaching, Emerging Tech, Tech Trends, Technology, Disruptive Technology, Professors, Oncology,