Christopher Quinn

  • Program Years: 2010-2014
  • Academic Institution: University of Illinois at Urbana-Champaign
  • Field of Study: Communications
  • Academic Advisor: Negar Kiyavash
  • Practicum(s):
    Sandia National Laboratories, California (2012)
  • Degree(s):
    Ph.D. Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 2014
    M.S. Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 2010
    B.S. Engineering Physics, Cornell University, 2008

Current Status

  • Status: Assistant Professor
  • Research Area: Information theory, stochastic networks, causal inference
  • Personal URL: http://web.ics.purdue.edu/~cjquinn/
  • Publications

    Journal:

    S. Kim, C. J. Quinn, N. Kiyavash, and T. Coleman, "Dynamic and succinct statistical analysis of neuroscience data," Proceedings of the IEEE, in press.

    C. J. Quinn, N. Kiyavash, and T. Coleman, “Directed Information Graphs,” submitted to IEEE Transactions on Information Theory, February 2014.

    C. J. Quinn, N. Kiyavash, and T. P. Coleman, “Efficient Methods to Compute Optimal Tree Approximations of Directed Information Graphs,” IEEE Transactions on Signal Processing, 61(12): 3173-3182, June 2013.

    D. G. Mixon, C. J. Quinn, N. Kiyavash, M. Fickus, “Fingerprinting with Equiangular Tight Frames,” IEEE Transactions on Information Theory, 59(3):1855-1865, March 2013.


    C. J. Quinn, T. P. Coleman, N. Kiyavash, and N. G. Hatsopoulos, “Estimating the directed information to infer causal relationships in ensemble neural spike train recordings,” Journal of Computational Neuroscience: Special Issue on Methods of Information Theory in Computational Neuroscience, 30(1): 17-44, 2011.


    Conference:

    C. J. Quinn, A. Pinar, and N. Kiyavash, “Optimal Bounded-Degree Approximations of Joint Distributions of Networks of Stochastic Processes,” IEEE International Symposium on Information Theory, July 2013.

    C. J. Quinn, J. Etesami, N. Kiyavash, and T. Coleman, “Sample Complexity for Inferring Directed Information Graphs,” IEEE International Symposium on Information Theory, July 2013.

    C. J. Quinn, N. Kiyavash, and T. P. Coleman, “A Minimal Approach to Causal Inference on Topologies with Bounded Indegree,” IEEE Conference on Decision and Control, December 2011.

    C. J. Quinn, N. Kiyavash, and T. P. Coleman, “Equivalence Between Minimal Generative Model Graphs and Directed Information Graphs,” IEEE International Symposium on Information Theory, July 2011.

    D.G. Mixon, C. J. Quinn, N. Kiyavash, and M. Fickus. “Equiangular tight frame fingerprinting codes”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2011.

    C. J. Quinn, N. Kiyavash, and T. P. Coleman, “A Generalized Prediction Framework for Granger Causality,” IEEE Infocom, NetSciCom Workshop, April 2011.

    C. J. Quinn, T. P. Coleman, and N. Kiyavash, “Approximating Discrete Probability Distributions with Causal Dependence Trees,” IEEE International Symposium on Information Theory and Applications (ISITA), October 2010.

    K.J. Cho, E. Hawkes, C. J. Quinn, R.J. Wood, “Design, fabrication and analysis of a body-caudal fin propulsion system for a microrobotic fish,” IEEE International Conference on Robotics and Automation 2008.

    Awards

    NSF GRFP Honorable Mention, Spring 2009, Spring 2010

    ECE Distinguished Fellowship, University of Illinois at Urbana-Champaign, 2008-2009

    McMullen Dean’s Scholar (Cornell Engineering), 2004-2008

    Dean’s List, Cornell (all semesters)

    Brown Brain Science Undergraduate Research Fellowship (summer 2005)

    Undergraduate Expository Writing Award (James E. Rice, Jr. Prize, FA 2005)