John Harer, Professor of Mathematics and Electrical and Computer Engineering

John Harer

Professor Harer's primary research is in the use of geometric, combinatorial and computational techniques to study a variety of problems in data analysis, shape recognition, image segmentation, tracking, brain imaging, biological networks and gene expression.

Office Location:  109 Physic Bldg, Durham, NC 27708
Office Phone:  (919) 660-2845
Email Address: send me a message
Web Page:  http://cms.math.duke.edu/harer/?q=home

Teaching (Fall 2017):

Education:

Ph.D.University of California at Berkeley1979
BSHaverford College1974
B.A.Harvard University1974
Specialties:

Topology
Geometry
Mathematical Biology
Applied Math
Research Interests: Computational Topology, Computational Biology, Algorithms

Current projects: Biochronicity, Computational Topology, Statistical Topology, Self-Healing Networks, Network Inference, Geometric Image Analysis

Professor Harer's primary research is in the use of geometric, combinatorial and computational techniques to study a variety of problems in data analysis, shape recognition, image segmentation, tracking, brain imaging, biological networks and gene expression.

Areas of Interest:

Computational Biology
Computational Topology
Dynamics on Networks
Algorithms

Keywords:

Algorithms • Automatic Data Processing • Biomass • Chromosome Mapping • Crosses, Genetic • Genome, Plant • Genotype • Image Processing, Computer-Assisted • Imaging, Three-Dimensional • Inbreeding • Models, Biological • Multivariate Analysis • Oryza sativa • Phenotype • Plant Roots • Principal Component Analysis • Quantitative Trait Loci • Quantitative Trait, Heritable • Recombination, Genetic • Reproducibility of Results • Software • Workflow

Current Ph.D. Students  

Postdocs Mentored

Recent Publications

  1. Bendich, P; Chin, SP; Clark, J; Desena, J; Harer, J; Munch, E; Newman, A; Porter, D; Rouse, D; Strawn, N; Watkins, A, Topological and statistical behavior classifiers for tracking applications, IEEE Transactions on Aerospace and Electronic Systems, vol. 52 no. 6 (December, 2016), pp. 2644-2661 [doi]  [abs]
  2. McGoff, KA; Guo, X; Deckard, A; Kelliher, CM; Leman, AR; Francey, LJ; Hogenesch, JB; Haase, SB; Harer, JL, The Local Edge Machine: inference of dynamic models of gene regulation., Genome Biology: biology for the post-genomic era, vol. 17 no. 1 (October, Submitted, 2016), pp. 214  [abs]
  3. Bendich, P; Gasparovic, E; Harer, J; Tralie, C, Geometric models for musical audio data, LIPIcs, vol. 51 (June, 2016), pp. 65.1-65.5, ISBN 9783959770095 [doi]  [abs]
  4. Bendich, P; Gasparovic, E; Harer, J; Izmailov, R; Ness, L, Multi-scale local shape analysis and feature selection in machine learning applications, Proceedings of the International Joint Conference on Neural Networks, vol. 2015-September (September, Accepted, 2015) [doi]  [abs]
  5. Perea, JA; Deckard, A; Haase, SB; Harer, J, SW1PerS: Sliding windows and 1-persistence scoring; discovering periodicity in gene expression time series data., BMC Bioinformatics, vol. 16 (August, 2015), pp. 257 [doi]  [abs]
Recent Grant Support