Christopher Quinn

  • Academic Institution: University of Illinois at Urbana-Champaign
  • Program Year: 3
  • Practicum(s):
    Sandia National Laboratories, California (2012)
  • Degree(s):
    B.S. Engineering Physics, Cornell University, 2008
  • Field of Study: Communications
  • Academic Advisor: Negar Kiyavash

Summary of Research:

Our work involves developing statistical methods to identify “who influences whom” in networks. Examples include neuroscience (“which cells connect to which cells”), social networks (“whose tweets are ‘viral’?”), and financial networks (“does the French GDP affect US housing prices?”).

The first component of our research is using an information-theoretic measure of causality, known as “directed information,” to quantify influence. This quantity embodies Granger causality, a well-established framework. We use this to define graphical models to meaningfully represent influences in a network.

The second component of our work involves developing algorithms to identify network structure from time series. We consider recovering the full graph structure as well as optimally approximating the graph structure. For instance, in online social networks, a user might have hundreds of friends; we might want to find which are the three most influential friends.

The third component of our work is data analysis. We performed an earlier study in neuroscience and continue to work in that area. We are now investigating social networks.

Publications:

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

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

C. Quinn, N. Kiyavash, and T. Coleman, “Directed Information Graphs,” submitted to IEEE Transactions on Information Theory, April 2012.

D. Mixon, C. Quinn, N. Kiyavash, and M. Fickus, “Equiangular Tight Frames for Fingerprinting,” revised and accepted for publication in IEEE Transactions on Information Theory, November 2012.

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

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

C. Quinn, T. P. Coleman and N. Kiyavash, “Efficient Methods to Compute Optimal Tree Approximations of Directed Information Graphs,” submitted to IEEE Transactions on Signal Processing, July 2012.

C. 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.

C. 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, June 2010.

K.J. Cho, E. Hawkes, C. 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)