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   Kevin R. Moon 
     Postdoctoral Associate
     Genetics Department and Applied Math Program
     Yale University
     Email: kevin.moon "at" yale.edu
     Office: 307 SHM and 104 AKW
      
      I am currently on the job market. Please contact me for an updated CV,               research statement, and teaching statement if interested.
     
     Curriculum Vitae: PDF (July 2016)

About Me

I am a postdoctoral associate at Yale University under Dr. Smita Krishnaswamy in the Genetics and Computer Science departments and Dr. Ronald Coifman in the Mathematics and Computer Science departments. I completed my PhD in Electrical Engineering and Computer Science (EECS) under Dr. Alfred Hero at the University of Michigan in Ann Arbor in 2016. I completed an MS (2016) in Mathematics at Michigan and an MS (2012) and BS (2011) in electrical engineering from Brigham Young University in Provo, Utah. During my undergraduate studies, I spent two years giving service in Puebla, Mexico and studied abroad in China for six weeks.

Research

My general research interests are in the development of theory and applications in machine learning, big data, information theory, manifold learning, statistical signal processing, statistical learning theory, estimation, graphical models, and random matrix theory. I am strongly interested in biological and medical applications.

My main projects currently focus on data visualization, data denoising, and nonparametric estimation of information theoretic measures such as entropy, mutual information, and  information divergence. Specific applications I am involved in include sunspot and active region images, neural data, and single-cell data. See my research page for more details.

Selected Publications

  1. K.R. Moon, D. van Dijk, Z. Wang, W. Chen, M.J. Hirn, R.R. Coifman, N.B. Ivanova, G. Wolf, S. Krishnaswamy, "Visualizing Transitions and Structure for High-Dimensional Data Exploration," 2017. (bioRxivcode)
  2. K.R. Moon, M. Noshad, S. Yasaei Sekeh, A. O. Hero III, "Information theoretic structure learning with confidence," IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 6095-6099, Mar. 2017. (Invited Paper), (arXiv)
  3. K.R Moon, K. Sricharan, K. Greenewald, A.O. Hero III, "Improving convergence of divergence functional ensemble estimators," IEEE International Symposium on Information Theory (ISIT), pp. 1133-1137, July 2016. (Link, long version at arXiv)
  4. K.R. Moon, V. Delouille, J.J. Li, R. De Visscher, F. Watson, and A.O. Hero III, "Image patch analysis of sunspots and active regions. II. Clustering via matrix factorization," Topical Issue on Statistical Challenges in Solar Information Processing, Journal of Space Weather and Space Climate, vol. 6, A3, Jan. 2016. (Linkarxiv)
  5. K.R. Moon, J.J. Li, V. Delouille, R. De Visscher, F. Watson, and A.O. Hero III, "Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis," Topical Issue on Statistical Challenges in Solar Information Processing, Journal of Space Weather and Space Climate, vol. 6, A2, Jan. 2016. (Linkarxiv)
A full list is found here or Google Scholar.

Awards and Honors

  • 2nd Place in Signal and Image Processing poster competition at 2015 Engineering Graduate Symposium at the University of Michigan
  • 3rd Place Best Student Paper Award at SPW 2015
  • Top 10% Paper Award at ICIP 2014
  • NSF Graduate Research Fellowship, 2012-2016
  • NSF Graduate Research Fellowship Honorable Mention, 2011
  • NASA Rocky Mountain Space Grant, 2011
  • Distinguished Student Award from BYU Math Department, 2011
  • Gordon B. Hinckley Presidential Scholar at BYU, 2005-2011
  • National Merit Scholar, 2005