University of Michigan Industrial and Operations Engineering (U-M IOE) G. Lawton and Louise G. Johnson Professor of Engineering, Jon Lee has been awarded a grant from AFOSR in the amount of $582,002 for his work on optimization for sensor networks.
University of Michigan Industrial and Operations Engineering (U-M IOE) G. Lawton and Louise G. Johnson Professor of Engineering, Jon Lee has been awarded a grant from the Air Force Office of Scientific Research (AFOSR) in the amount of $582,002 for his work on optimization for sensor networks. The project is entitled “Maximum-entropy Sampling for Sensor Networks: Graphical Models, Algorithmics, and Generalizations.”
Sensor networks are essential to the growing infrastructure for the collection of data. Lee is investigating the problem of determining the optimal set of locations for sensors, in any given system.
The mathematics that is at the center of this research, the so-called “differential entropy”, is a fundamental concept in information theory, introduced by the luminary Claude Shannon in 1948. Shannon got his undergraduate degrees at U-M, in electrical engineering and in mathematics, in 1936.
“I have been working on algorithmics associated with this concept for three decades,” Lee said. “I am deeply grateful to the Complex Networks program of the Air Force Office of Scientific Research for enabling me to continue to robustly work on this fundamental topic. Our technical approach is based on advanced techniques of mathematical optimization and data analysis. In that context, there is no standard algorithm for handling our problem.”
Lee and his colleagues are working to develop new techniques to account for the complex nature of their formulation. One key structure that they are exploiting is the idea of sparse graphical models, which account for weak coupling between distant pairs of sensors.