Current core R&D: Bayesian statistics and decision analysis in causal inference, dynamic modeling, forecasting & time series analysis, dynamic networks, model uncertainty, simulation & optimization. Current applied R&D: financial forecasting & portfolio decisions, macroeconomic forecasting for policy decisions, forecasting & casual inference for decisions in commercial settings, dynamic networks and anomaly detection. Continuing (not currently so active) interests: biomedical and engineering signal processing, climatology, genomics & biostatistics, neuroscience.
Background
The Arts & Sciences Distinguished Professor Emeritus of Statistics & Decision Sciences at Duke University; Research interests include Bayesian statistics and decision analysis in causal inference, dynamic modeling, forecasting & time series analysis, dynamic networks, model uncertainty, simulation & optimization.