Jennifer Gamble


I am in my final year of PhD studies in Electrical Engineering at NCSU, under Dr. Hamid Krim. My BSc in Mathematics and MSc in Statistics were obtained from the University of Alberta in Edmonton, Canada. My MSc supervisor was Dr. Giseon Heo, who I continued to work with for two years as a research associate, performing research as well as statistical consulting for the U of A Department of Medicine and Dentistry. Our research involved the use of methods from computational topology for statistical shape analysis (with applications to three-dimensional orthodontic data sets).

In my doctoral research, I use methods from applied topology to study dynamic and complex networks. These networks are represented as simplicial complexes, and topological properties of the complexes are used to derive properties of the associated graphs and their underlying structures. One major project assesses coverage in time-varying sensor networks using only coordinate-free data about the communication graph. Another project is in the area of social network analysis, which uses a topology-preserving collapse based on the local property of ‘node dominance’, and has applications in both community detection and core-periphery decomposition. Broadly, my research interests include network analysis, data analysis, and machine learning, with emphasis on geometrically- and topologically-informed feature extraction.


  • Gamble, J. Chintakunta, H. and Krim, H. Adaptive tracking of representative cycles in regular and zigzag persistent homology. Preprint: arxiv:1411.5442, 2014. [pdf]
  • Gamble, J. Chintakunta, H. and Krim, H. Coordinate-free quantification of coverage in dynamic sensor networks. Preprint: arxiv:1411.7337, 2014. [pdf]
  • Gamble, J. Chintakunta, H. Krim, H. Emergence of core-periphery structure from local node dominance in social networks. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).2015. (submitted)
  • Gamble, J. Chintakunta, H. Krim, H. Applied topology in static and dynamic sensor networks. IEEE 2012 International Conference on Signal Processing and Communications (SPCOM). 2012.  [pdf]
  • Heo, G, Gamble, J, Kim, P. Topological analysis of variance and the maxillary complex. J Am Stat Assoc. 2012 Jul; 107(498):477-492. [pdf]
  • Gamble J, Heo G. Exploring uses of persistent homology for statistical analysis of landmark-based shape data. JMultivariate Anal. 2010 Oct; 101(9):2184-2199. [pdf]