The Laboratory for Information and Decision Systems (LIDS) is an interdepartmental laboratory for research and education in systems, control, optimization, communication, networks, and statistical signal processing. These disciplines, which span the domain of the analytical information and decision sciences, play a critical and pervasive role in science, engineering, and society.
LIDS provides a melting pot of disciplines that share a common approach to problems, a common mathematical base, and an energized environment. This kind of milieu not only fosters inspired thinking and research but also encourages and enables students to build disciplinary depth and interdisciplinary understanding essential for research and engineering leadership.
LIDS continues to be a world-recognized leading research organization as evidenced by some of its recent events. The Symposium on Paths Ahead in the Science of Information and Decision Systems, held in November 2009 and organized by LIDS was a major international event, attended by 340+ researchers from around the world, including many of the most recognized names in the field. Read more about this event at the Paths Ahead website, which also includes a brief history of LIDS.
In addition, LIDS faculty and students continue to receive substantial recognition for their contributions, with numerous national and international awards. The LIDS website contains details on LIDS activities, people, awards, and research accomplishments and directions, some of which are highlighted below. Read about these and other research projects and get a feel for LIDS culture by reading LIDSALL, the online annual LIDS newsletter.
Some LIDS Research Project highlights:
A new and very simple algorithm for medium access control for wireless networks, achieving performance that has been sought for 4 decades. Prof. Devavrat Shah and his students have developed new algorithms that achieve the best possible performance for medium access control. The algorithm is completely distributed and very simple to implement and operate.
Investigation of information propagation and learning in social networks and characterization of properties of such networks that can lead to distinctly different observed patterns of behavior. Read more about this work of LIDS faculty Asuman Ozdaglar and Munther Dahleh and Economics Dept. faculty Daron Acemoglu.
Development of new statistical/machine learning methods capable of discovering multiple modes of dynamic behavior in complex data. Former EECS/LIDS graduate student, Dr. Emily Fox (now at Duke) and her advisor, Prof. Alan Willsky, developed new statistical methods for discovering complex modes of behavior of dynamic phenomena, including switching between different behaviors – in this case the motion of honeybees, which exhibit distinctive behavior (circling one way or the other and “waggling”). This method has been applied to a wide variety of data sets including stock index time series and human exercise routines.)
A continuation of the long history of the world-leading contributions of LIDS researchers in optimization algorithms, including the application of these methods to numerous domains, such as the optimal design of materials for wave propagation (See the illustration in the slideshow above of the application of advanced methods of optimization, developed by Prof. Pablo Parrilo and his students, to the design of materials with desired spectral bandgap properties.)
Led by Prof. Emilio Frazzoli and Prof. Patrick Jaillet, and with involvement of other MIT faculty and researchers, LIDS is playing a significant role in the recently-initiated program on future urban mobility, funded by Singapore. This program is intended to look at a broad agenda, ranging from tackling problems of exploiting fine-grained information through the increasingly powerful internet and explosion of personal devices and devices located on individual vehicles, to developing integrated models for use in planning of land, resource, and energy use.