Statistics and Data Science
While mechanistic models may exist for some physical systems, they often overlook how users of these systems actually make decisions. Furthermore, the emergence of new technologies enabling the Internet of Things (IoT), mobile devices, and big data presents us with new opportunities to understand both physical systems and social behavior. The key issue is how to generate reliable and actionable algorithms and models from diverse data with only partial information about the underlying processes. New and powerful techniques in modern statistics as well as machine learning algorithms are needed to support these applications. A powerful use for such models is prediction. Given the complexity of the underlying applications, prediction methods will continue to be limited by the ‘curse of dimensionality’ and will demand new innovations in experimental design, computation, and model reduction.
Information and Decision Theory
Information and decision theory is a broad discipline that includes research in: systems and controls, optimization and game theory, networks, and inference and statistical data processing. Systems and control theory addresses the challenges associated with designing, modeling and controlling complex, distributed systems. Optimization and games are powerful techniques for arriving at synthesis, and addressing algorithms for single or multiple decision makers. Communications and networks research focuses on issues of performance (discovering both fundamental limitations, and close-to-optimal methods), as well as scalability (i.e., maintaining information and algorithmic efficiency as network size increases). Inference and statistical data processing looks at estimation and learning in dynamical systems, for example: estimating the state of a dynamical system or identifying a dynamic model for such a system.
Human and Institutional Behavior
At IDSS, research into the behaviors of humans and institutions looks at nontraditional aspects of modeling these behaviors as they relate to particular societal issues. This includes the behavior of individuals, groups, and institutions (such as markets, regulators, and governments) as it impacts upon the operation and behavior of systems. Aspects of this field are anchored in the social sciences, e.g., economics, sociology, psychology, political science, management and policy. The availability of large amounts of data on individual and institutional behavior will enable empirical models to be derived that are consistent with fundamental theory, and actionable from an analysis and design perspective. Topics include: rational decision theory, behavioral decision theory, organizational behavior, and public policy design.