I lead multidisciplinary efforts with teams of researchers, applied scientists and engineers working at the intersection of machine learning and natural language processing. My current work focuses on making large-scale AI models more efficient in terms of (1) computational needs and (2) the amounts of supervision needed to learn to perform a new task. Our work spans both research and engineering where we advance the state-of-the-art and create horizontal technology that enables teams of scientists and developers to use large-scale AI in practice. My earlier work spanned topics including information extraction, summarization, measuring and improving search systems via user behavior modeling and building natural language interfaces to services and data. I co-authored a 100+ peer-reviewed publications in Machine Learning, Natural Language Processing and Information Retrieval and I am a co-inventor on 40+ US patents. I regularly serves as (senior) committee, area chair, guest editor and editorial board member at many major ML, NLP and IR venues. My contributions to NLP and IR have been recently recognized with the 2020 Karen Spärck Jones Award.