John Harer

John Harer
  • Professor of Mathematics
External address: 109 Physic Bldg, Durham, NC 27708
Internal office address: Box 90320, Durham, NC 27708-0034
Phone: (919) 660-2845

Research Areas and Keywords

Biological Modeling

Gene Regulatory Networks, Network Inference

Computational Mathematics

Topological Data Analysis,
Geometric Data Analysis,
Network Dynamics,
Network Inference

Signals, Images & Data

Topological Data Analysis,
Geometric Data Analysis


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

Education & Training
  • Ph.D., University of California - Berkeley 1979

  • B.A., Haverford College 1974

Selected Grants

Geometric and Topological Methods for Multi-Modal Data Analysis and Fusion awarded by Air Force Office of Scientific Research (Principal Investigator). 2018 to 2021

BIGDATA: F: DKA: CSD: Topological Data Analysis and Machine-Learning with Community-Accepted Features awarded by National Science Foundation (Principal Investigator). 2014 to 2019

Quantifying Complex Spatiotemporal Systems awarded by Rutgers, The State University of New Jersey (Principal Investigator). 2016 to 2018

EMSW21-RTG: Geometric, Topological and Statistical Methods for Analyzing Massive Datasets awarded by National Science Foundation (Principal Investigator). 2011 to 2018

Foundation of Information Systems awarded by Johns Hopkins University (Principal Investigator). 2012 to 2017

Analysis of High Dimensional Complex Spatio-Temporal Data awarded by Defense Advanced Research Projects Agency (Principal Investigator). 2015 to 2016

Inferring Network Controls from Topology Using the CHomP Database awarded by Air Force Office of Scientific Research (Principal Investigator). 2010 to 2015

A Multidimensional Imaging Platform to Analyze Crop Root System Dynamics in Response to Changing Environments awarded by Department of Agriculture (Co-Principal Investigator). 2011 to 2013

GEPR: Genome-wide analysis of root traits awarded by National Science Foundation (Co-Principal Investigator). 2008 to 2012


Edelsbrunner, Herbert, and John Harer. Computational Topology - an Introduction. American Mathematical Society, 2010.

Smith, Lauren M., et al. “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. 754–59. Epmc, doi:10.1126/science.aba4357. Full Text

Bendich, P., et al. Scaffoldings and Spines: Organizing High-Dimensional Data Using Cover Trees, Local Principal Component Analysis, and Persistent Homology. Vol. 13, Jan. 2018, pp. 93–114. Scopus, doi:10.1007/978-3-319-89593-2_6. Full Text

Hughes, Michael E., et al. “Guidelines for Genome-Scale Analysis of Biological Rhythms.Journal of Biological Rhythms, vol. 32, no. 5, Oct. 2017, pp. 380–93. Epmc, doi:10.1177/0748730417728663. Full Text

Bendich, P., et al. “Topological and statistical behavior classifiers for tracking applications.” Ieee Transactions on Aerospace and Electronic Systems, vol. 52, no. 6, Dec. 2016, pp. 2644–61. Scopus, doi:10.1109/TAES.2016.160405. Full Text

McGoff, Kevin A., et al. “The Local Edge Machine: inference of dynamic models of gene regulation.Genome Biology, vol. 17, no. 1, Oct. 2016, p. 214. Epmc, doi:10.1186/s13059-016-1076-z. Full Text

Perea, Jose A., et al. “SW1PerS: Sliding windows and 1-persistence scoring; discovering periodicity in gene expression time series data.Bmc Bioinformatics, vol. 16, Aug. 2015, p. 257. Epmc, doi:10.1186/s12859-015-0645-6. Full Text

Perea, J. A., and J. Harer. “Sliding Windows and Persistence: An Application of Topological Methods to Signal Analysis.” Foundations of Computational Mathematics, vol. 15, no. 3, June 2015, pp. 799–838. Scopus, doi:10.1007/s10208-014-9206-z. Full Text

Munch, E., et al. “Probabilistic Fréchet means for time varying persistence diagrams.” Electronic Journal of Statistics, vol. 9, Jan. 2015, pp. 1173–204. Scopus, doi:10.1214/15-EJS1030. Full Text Open Access Copy

Farr, Robert S., et al. “Easily repairable networks: reconnecting nodes after damage.Physical Review Letters, vol. 113, no. 13, Sept. 2014, p. 138701. Epmc, doi:10.1103/physrevlett.113.138701. Full Text

Bristow, Sara L., et al. “Checkpoints couple transcription network oscillator dynamics to cell-cycle progression.Genome Biology, vol. 15, no. 9, Sept. 2014, p. 446. Epmc, doi:10.1186/s13059-014-0446-7. Full Text


Tralie, C. J., et al. “Multi-Scale Geometric Summaries for Similarity-Based Sensor Fusion.” Ieee Aerospace Conference Proceedings, vol. 2019-March, 2019. Scopus, doi:10.1109/AERO.2019.8741399. Full Text

Tralie, C. J., et al. “Geometric cross-modal comparison of heterogeneous sensor data.” Ieee Aerospace Conference Proceedings, vol. 2018-March, 2018, pp. 1–10. Scopus, doi:10.1109/AERO.2018.8396789. Full Text Open Access Copy

Garagić, D., et al. “Upstream fusion of multiple sensing modalities using machine learning and topological analysis: An initial exploration.” Ieee Aerospace Conference Proceedings, vol. 2018-March, 2018, pp. 1–8. Scopus, doi:10.1109/AERO.2018.8396737. Full Text

Bendich, P., et al. “Geometric models for musical audio data.” Leibniz International Proceedings in Informatics, Lipics, vol. 51, 2016, pp. 65.1-65.5. Scopus, doi:10.4230/LIPIcs.SoCG.2016.65. Full Text Open Access Copy

Bendich, P., et al. “Geometric Models for Musical Audio Data.” Proceedings of the 32st International Symposium on Computational Geometry (Socg), 2016.

Bendich, P., et al. “Multi-scale local shape analysis and feature selection in machine learning applications.” Proceedings of the International Joint Conference on Neural Networks, vol. 2015-September, 2015. Scopus, doi:10.1109/IJCNN.2015.7280428. Full Text Open Access Copy

Rouse, D., et al. “Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers.” Proceedings of Spie  the International Society for Optical Engineering, vol. 9474, 2015. Scopus, doi:10.1117/12.2179555. Full Text

Edelsbrunner, Herbert, and John Harer. “Persistent homology - a survey.” Surveys on Discrete and Computational Geometry: Twenty Years Later, edited by J. E. Goodman et al., vol. 453, AMER MATHEMATICAL SOC, 2008, pp. 257-+.

Czumaj, Artur, and Christian Sohler. “Testing Expansion in Bounded-Degree Graphs.” 48th Annual Ieee Symposium on Foundations of Computer Science (Focs’07), IEEE, 2007. Crossref, doi:10.1109/focs.2007.33. Full Text

Bendich, Paul, et al. “Inferring Local Homology from Sampled Stratified Spaces.” 48th Annual Ieee Symposium on Foundations of Computer Science (Focs’07), IEEE, 2007. Crossref, doi:10.1109/focs.2007.45. Full Text

Pool testing at Duke - Professor John Harer

Students returning to Duke University are participating in surveillance testing to help rapidly identify and isolate people who may have contracted the COVID-19 virus. This is done using pool testing, which combines nasal samples from five people... read more »

Former Graduate Students

  • Anne Collins (01/2002 - 01/2006): Configuration Spaces in Robotic Manipulation and Motion Planning