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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, cyber security, ioT, biological networks and gene expression.

Contact Info:
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 2020):

  • MATH 412.01, TOPOLOGICAL DATA ANALYSIS Synopsis
    Online ON, TuTh 01:45 PM-03:00 PM
    (also cross-listed as COMPSCI 434.01)
  • MATH 713.01, TOPOLOGICAL DATA ANALYSIS Synopsis
    Online ON, TuTh 01:45 PM-03:00 PM
Education:

Ph.D.University of California - Berkeley1979
BSHaverford College1974
B.A.Haverford College1974
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

Curriculum Vitae
Current Ph.D. Students   (Former Students)

  • Christopher Traile  
  • Hamza Ghadyali  
  • Colbert Sesanker  
  • Darryl Wade  
Postdocs Mentored

  • Henry Adams (2014 - 2015)  
  • Francis Motta (2014/12-present)  
  • Justin Curry (2014/12-present)  
  • Anastasia Deckard (2014/12-present)  
  • Ellen Gasparovic (2013 - 2015)  
  • Xin Guo (2013 - 2014)  
  • Xin Guo (2013 - 2015)  
  • Omer Bobrowski (2012 - 2014)  
  • Joshua Vogelstein (2012 - 2014)  
  • Jurgen Sladeczek (2011 - 2015)  
  • Jose' Perea (2011 - 2015)  
  • Kevin McGoff (2011 - 2015)  
  • Nate Strawn (2011 - 2015)  
  • Paul Bendich (January 01, 2011 - present)  
  • Chris Topp (2009 - 2011)  
  • Anjali Iyer-Pascuzzi (2007 - 2011)  
  • Yuriy Mileyko (2008 - 2011)  
Recent Publications   (More Publications)

  1. Smith, LM; Motta, FC; Chopra, G; Moch, JK; Nerem, RR; Cummins, B; Roche, KE; Kelliher, CM; Leman, AR; Harer, J; Gedeon, T; Waters, NC; Haase, SB, An intrinsic oscillator drives the blood stage cycle of the malaria parasite Plasmodium falciparum., Science (New York, N.Y.), vol. 368 no. 6492 (May, 2020), pp. 754-759 [doi]  [abs]
  2. Tralie, CJ; Bendich, P; Harer, J, Multi-Scale Geometric Summaries for Similarity-Based Sensor Fusion, Ieee Aerospace Conference Proceedings, vol. 2019-March (March, 2019), ISBN 9781538668542 [doi]  [abs]
  3. Tralie, CJ; Smith, A; Borggren, N; Hineman, J; Bendich, P; Zulch, P; Harer, J, Geometric cross-modal comparison of heterogeneous sensor data, Ieee Aerospace Conference Proceedings, vol. 2018-March (June, 2018), pp. 1-10, IEEE, ISBN 9781538620144 [doi]  [abs]
  4. Garagić, D; Peskoe, J; Liu, F; Claffey, MS; Bendich, P; Hineman, J; Borggren, N; Harer, J; Zulch, P; Rhodes, BJ, Upstream fusion of multiple sensing modalities using machine learning and topological analysis: An initial exploration, Ieee Aerospace Conference Proceedings, vol. 2018-March (June, 2018), pp. 1-8, IEEE, ISBN 9781538620144 [doi]  [abs]
  5. Bendich, P; Gasparovic, E; Harer, J; Tralie, CJ, Scaffoldings and Spines: Organizing High-Dimensional Data Using Cover Trees, Local Principal Component Analysis, and Persistent Homology, vol. 13 (January, 2018), pp. 93-114 [doi]  [abs]
Recent Grant Support

  • Geometric and Topological Methods for Multi-Modal Data Analysis and Fusion, Air Force Office of Scientific Research, FA9550-18-1-0266, 2018/06-2021/06.      
  • Geometric and Topological Methods for Multi-Modal Data Analysis and Fusion, Air Force Office of Scientific Research, FA9550-18-1-0266, 2018/06-2021/06.      
  • BIGDATA: F: DKA: CSD: Topological Data Analysis and Machine-Learning with Community-Accepted Features, National Science Foundation, IIS-1447491, 2014/09-2019/08.      
  • BIGDATA: F: DKA: CSD: Topological Data Analysis and Machine-Learning with Community-Accepted Features, National Science Foundation, IIS-1447491, 2014/09-2019/08.      
  • Quantifying Complex Spatiotemporal Systems, Rutgers, The State University of New Jersey, 2016/08-2018/07.      
  • EMSW21-RTG: Geometric, Topological and Statistical Methods for Analyzing Massive Datasets, National Science Foundation, DMS-1045153, 2011/08-2018/07.      

 

dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320