Laboratory for Information and Decision Systems

The Laboratory for Information and Decision Systems (LIDS) is an interdepartmental laboratory for research and education in systems, networks, and control. LIDS is staffed by faculty, research scientists, and graduate students from the departments of Electrical Engineering and Computer Science, Aeronautics and Astronautics, and Mechanical Engineering, as well as the Sloan School of Management. LIDS research falls into four main areas.

Research in Networks includes research on communication networks and information theory. The work extends to applications in satellite, wireless and optical communications, and data networks. In addition, major new directions include the analysis of social networks and of interactions among networked systems and/or agents, with applications ranging from analysis of data from large-scale social networks to the dynamics and risk in large interconnected financial, transportation, and power systems.

The Statistical Inference and Machine Learning group analyzes complex systems, phenomena, and data subject to uncertainty and statistical variability. Research ranges from basic theory, methodologies, and algorithms to challenging applications in a broad array of fields. Applications include multi-sensor data assimilation for earth sciences, biomedical image analysis, object recognition and computer vision, and discovery of complex interactions and behaviors in video and other data sources.

Work in Optimization looks at analytical and computational methods for solving optimization problems arising in engineering and operations research. It has applications in communication networks, control theory, power systems, machine learning, and computer-aided manufacturing. In addition to linear, nonlinear, dynamic, convex, and network programming, the solution of large-scale problems exploiting algebraic structure and simulation-based methods is examined.

The Control and System Theory group deals with all aspects of systems analysis, including learning and system identification, controller design and optimization, and analysis of distributed systems involving the interaction of information and control. Theoretical research quantifies fundamental capabilities of learning and feedback control in the presence of uncertainty. Applications include control architectures for unmanned vehicles and controllers for semiconductor manufacturing.

For further information, contact LIDS associate director, Professor Pablo Parrilo, Room 32D-726, 617-324-1542.