Principal Investigator Alex 'Sandy' Pentland
Co-investigators Stephen Buckley , Thomas Hardjono , Asuman Ozdaglar , Harold Abelson , K Acemoglu , David Clark , Munther Dahleh , Konstantinos Daskalakis , Olivier deWeck , Vivek Farias , John Fisher , Jeffrey Jaffe , Patrick Jaillet , David Karger , Kent Larson , Andrew Lo , Stuart Madnick , Silvio Micali , Robert Miller , Aran M Parillo , Parag Pathak , Devavrat Shah , Anthony Sinskey , William Uricchio , John Williams , Ethan Zuckerman
Project Website http://connection.mit.edu/
As more of our personal and public lives become infused and shaped by data from sensors and computing devices, the lines between the digital and the physical have become increasingly blurred. New possibilities arise, some promising, others alarming, but both with an inexorable momentum that is supplanting time honored practices and institutions. MIT Connection Science is a cross-disciplinary effort drawing on the strengths of faculty, departments and researchers across the Institute, to decode the meaning of this dynamic, at times chaotic, new environment. The initiative will help business executives, investors, entrepreneurs and policymakers capitalize on the multitude of opportunities unlocked by the new hyperconnected world we live in.
MIT Connection Scienceis improving organizations through deep insights into human behavior and targeted interventions that leverage human networks. With applicaitons ranging from energy to financial services to social adoption of new ideas, MIT Connection Science design better tools to foster a better society.
The mission of MIT Connection Science is to revolutionize technology-mediated human networks through analysis, prediction, data-driven design and evaluation. The research agenda spans the scale of human endeavor from small groupings to entire nation-states.
A union of network theory, opreations research, control and systems theorym computer science, economics, behavioral science, and social media.
Area of research include:
Modeling Social Network Flows (*) Understand information flows, influence, and cascades (*) A holisitic approach to stability and effects of network structure
Social Data (*) Living labs to collect data and validate theories (*) Modeling of experimental and observed data
Theory of Network Computation (*) Scalable algorithms for large network optimization (*) Tractable algorithms for detection and inference in large networks
Network Mechanism Design (*) Designing social incentives (*) Control over large and evolving networks
Social Architectures (*) New applications and architectures for efficient and large-scale crowd sourcing (*) Engineering more flexible architectures for interconnection of social and technological networks