Professor Silvia Ferrari

silvia_ferrari

Professor

Mechanical and Aerospace Engineering

Director

Laboratory for Intelligent Systems and Controls

Contact Information

Sibley School of Mechanical and Aerospace Engineering Cornell University
543 Upson Hall • Ithaca, NY 14853
Phone:  (607) 255-4216

Professor Ferrari’s research aims at providing intelligent control systems with a higher degree of mathematical structure to guide their application and improve reliability. Decision-making processes are automated based on concepts drawn from control theory and the life sciences. Recent efforts have focused on optimal control problems in computational geometry and multiscale dynamical systems aimed at improving the effectiveness of mobile sensor networks, such as, acoustic and demining sensors installed on underwater vehicles and ground robots.  New methods for neural network training are also being developed to retain long-term procedural memories, solving partial differential equations online, and training in-vitro and in-silico spiking neural networks to solve complex sensorimotor learning problems.

Principal research efforts

  • Approximate dynamic programming
  • Learning in neural and Bayesian networks
  • Sensor path planning
  • Integrated surveillance systems
  • Reconfigurable control of aircraft
  • Intelligent systems for criminal profiling

Education

  • Princeton University, Princeton, NJ
    Ph.D., Mechanical and Aerospace Engineering, November 2002
    M.A., Mechanical and Aerospace Engineering, November 1999
  • Embry-Riddle Aeronautical University, Daytona Beach, FL
    B.S., Aerospace Engineering, summa cum laude, May 1997

Recent Honors and Awards

  • Presidential Early Career Award for Scientists and Engineers (PECASE), 2006
  • International Crime Analysis Association Research Award, 2005
  • National Science Foundation CAREER Award, 2005
  • Office of Naval Research Young Investigator Award, 2004

Publications

Click here to access Prof. Ferrari’s publications.

Courses

  • MAE 6790: Intelligent Sensor Planning and Control