David S. Matteson is Associate Professor and Associate Department Chair of Statistics and Data Science and at Cornell University, where he is a member of the ILR School, Computing and Information Science, the Center for Applied Mathematics, the Fields of Computer Science and Operations Research, and the Program in Financial Engineering. Professor Matteson received his PhD in Statistics from the University of Chicago and his BSB in Finance, Mathematics, and Statistics from the University of Minnesota. He received a CAREER Award from the National Science Foundation (2015), the Chancellor’s Award for Scholarship and Creative Activities from the State University of New York (SUNY, 2022), the Ann S. Bowers Research Excellence Award from the Bowers College of Computing and Information Science (2022), Faculty Research Awards from the Xerox/PARC Foundation (2014) and LinkedIn (2022), and he and his students have received numerous Best Paper Awards.
He is currently founding Editor-in-Chief for Data Science in Science and an Associate Editor for the Journal of Econometrics and Statistica Sinica, as well as a former Associate Editor for the Journal of the American Statistical Association-Theory & Methods, The American Statistician, and Biometrics. He is an elected Officer for the Business and Economic Statistics Section of the American Statistical Association, a member of the Institute of Mathematical Statistics, the International Biometric Society, the International Society for Bayesian Analysis, the Association for Computing Machinery, the Society for Industrial and Applied Mathematics, and the American Geophysical Union. He is coauthor of Statistics and Data Analysis for Financial Engineering, and MOOC instructor for Introduction to Time Series Analysis.
He is lead PI and Director of the NSF funded PRISM Institute for Trans-domain Systemic Risk, lead PI and co-Director of the NSF funded TRIPODS Greater Data Science Cooperative Institute (GDSC), co-PI of the NSF funded Atomic-Level Structural Dynamics in Catalysts Institute, co-PI of a USAID funded Feed-the-Future team, an Executive Committee Member for the Cornell Center for Data Science for Enterprise & Society, and a Visiting Scholar at the Institute for Mathematics and its Applications. He is also a strong supporter of the National Institute of Statistical Sciences and its mission.
Research Theory & Methods: Changepoints, High Dimensional Time Series, Functional Data, Dependence Measures, Varying Parameters, Anomaly Detection, Constrained Estimation, State-Space Models, Geostatistics, Stochastic Volatility, Networks & Graphs, Domain Adaptation.
Research Applications: Financial Econometrics, Developmental Economics, Systemic Risk, Emergency Medical Services, Urban Informatics, Neuro Imaging and Signals, Applied Biophysics, Sustainable Energy, Ecology, Climate, Nanoparticles, Single Molecule Experiments, Epidemiology, Disability Studies, Space Science.