Postdoctoral Associate
Massachusetts Institute of Technology

Email: okosut at mit dot edu
Office: 32-D558

Biography

Oliver Kosut was born in California in 1982. He received B.S. degrees in Electrical Engineering and Mathematics from MIT in 2004. He received a Ph.D. from Cornell University in 2010, with advisor Professor Lang Tong. Since August 2010 he has been a post-doc in the Stochastic Systems Group at MIT.

Interests

Oliver's academic interests include:

• Information theory
• Security
• Power systems and smart grids
• Sampling
• Graphical models
• Sparse recovery

Oliver's non-academic interests include

• Puzzles
• Change-ringing
• Juggling
• Square dancing

Teaching

• Fall 2009: Co-instructor for "Topics on Power Networks and Smart Grids"
  
• Spring 2007: Teaching Assistant for "Detection and Estimation"
  
• Spring 2005: Teaching Assistant for "Solid State Circuits"
  

Dissertation

• "Adversaries in Networks"
  Cornell University Ph.D. dissertation

Journal Publications

• "On the dispersions of three network information theory problems"
  V. Y. F. Tan and O. Kosut
  submitted to IEEE Trans. on Information Theory, Jan. 2012


• "Polytope Codes against adversaries in networks"
  O. Kosut, L. Tong, and D. Tse
  submitted to IEEE Trans. on Information Theory, Dec. 2011


• "Malicious data attacks on the smart grid"
  O. Kosut, L. Jia, R. J. Thomas, L. Tong
  IEEE Trans. on Smart Grid, vol. 2, pp. 645–658, Oct. 2011


• "Distributed source coding in the presence of Byzantine sensors"
  O. Kosut and L. Tong
  IEEE Trans. on Information Theory, vol. 54, pp. 2550–2565, June 2008

Conference Publications

• "Malicious data attacks on smart grid state estimation: attack strategies and countermeasures"
  O. Kosut, L. Jia, R. J. Thomas, L. Tong
  in Proc. First International Conference on Smart Grid Communications, Oct. 2010


• "On malicious data attacks on power system state estimation"
  O. Kosut, L. Jia, R. J. Thomas, L. Tong
  in Proc. of 45th International Universities Power Engineering Conference, Aug.–Sep. 2010


• "Polytope codes against adversaries in networks"
  O. Kosut, L. Tong, and D. Tse
  in Proc. IEEE International Symposium on Information Theory, June 2010
  Finalist for Student Paper Award
  


• "Limiting false data attacks on power system state estimation"
  O. Kosut, L. Jia, R. Thomas, and L. Tong
  in Proc. of Conference on Information Sciences and Systems, Mar. 2010


• "Nonlinear network coding is necessary to combat general Byzantine attacks"
  O. Kosut, L. Tong, and D. Tse
  in Proc. of 47th Annual Allerton Conference on Communication, Control, and Computing, Oct. 2009


• "The quadratic Gaussian CEO problem with Byzantine agents"
  O. Kosut and L. Tong
  in Proc. of IEEE International Symposium on Information Theory, June–July 2009
  Finalist for Student Paper Award


• "A characterization of the error exponent for the Byzantine CEO problem"
  O. Kosut and L. Tong
  in Proc. of 46th Allerton Conference on Communication, Control and Computing, Sep. 2008


• "The Byzantine CEO problem"
  O. Kosut and L. Tong
  in Proc. of IEEE International Symposium on Information Theory, July 2008


• "The nose of a bloodhound: target chasing aided by a static sensor network"
  O. Kosut and L. Tong
  in Proc. of Asilomar Conference on Signals, Systems, and Computers, Nov. 2007


• "Integrated mobile and static sensing for target tracking"
  O. Kosut, A. Turovsky, J. Sun, M. Ezovski, G. Whipps, and L. Tong
  in Proc. of Military Communications Conference, June 2007


• "Variable-rate distributed source coding in the presence of Byzantine sensors"
  O. Kosut and L. Tong
  in Proc. of IEEE International Symposium on Information Theory, June 2007
  Finalist for Student Paper Award


• "Capacity of cooperative fusion in the presence of Byzantine sensors"
  O. Kosut and L. Tong
  in Proc. 44th Annual Allerton Conf. on Commununication, Control and Computation, Sep. 2006

Papers in Preparation

• "Tractable subgraphs-based iterative sampling for Gaussian graphical models"
  Y. Liu, O. Kosut, and A. Willsky


• "Sparse recovery with forward model uncertainty based on ellipsoid parameterization"
  O. Kosut, J. Saunderson, and A. Willsky