Machine learning, data science, causal inference, computational social science.
Professor Jensen's research focuses on machine learning and data science for analyzing large social, technological, and computational systems. His current research focuses on methods for constructing accurate causal models from observational and experimental data, with applications to social science, fraud detection, security, and systems management. Additional research interests include explainable machine learning, statistical relational learning, research methods in computer science, evaluation of machine learning systems, and data science for public policy and social good.
D.Sc. Engineering and Policy, Washington University (1992); M.S. Engineering and Policy, Washington University (1988); B.S. Mechanical Engineering, University of Nebraska (1986). From 1991 until 1995, Jensen was an analyst with the Office of Technology Assessment, an analytical agency of the United States Congress.
Professor Jensen directs the Knowledge Discovery Laboratory, which he founded in 2000, and he serves as Associate Director of the UMass Computational Social Science Institute. He regularly serves on program committees for several conferences, including the International Conference on Machine Learning, the Conference on Uncertainty in Artificial Intelligence, the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, and the IEEE International Conference on Data Mining. He served on the Board of Directors of the ACM Special Interest Group on Knowledge Discovery and Data Mining (2005-2013), the Defense Science Study Group (2006-2007), and DARPA's Information Science and Technology Group (2007-2012). In 2011, he received the Outstanding Teacher Award from the UMass College of Natural Sciences.