His interdisciplinary research focuses on large and scalable language analyses for health and social sciences. Utilizing natural language processing and machine learning techniques he seeks to discover new behavioral and psychological factors of health and well-being as manifest through language in social media. From 2012 to 2015, he was Lead Research Scientist for the World Well-Being Project at the University of Pennsylvania, an interdisciplinary team that grew to 15 full-time researchers studying how big language analyses can reveal and predict differences in health, personality, and well-being. He received his PhD in Computer Science from the University of Central Florida in 2011 with research on acquiring lexical semantic knowledge from the Web. His work has been featured in The New York Times, Wired, and The Washington Post.