John Harer
 Professor of Mathematics
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
Topology
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.
Selected Grants
Geometric and Topological Methods for MultiModal 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 MachineLearning with CommunityAccepted 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
EMSW21RTG: Geometric, Topological and Statistical Methods for Analyzing Massive Datasets awarded by National Science Foundation (Principal Investigator). 2011 to 2018
ATD: Online Multiscale Algorithms for Geometric Density Estimation in HighDimensions and Persistent Homology of Data for Improved Threat awarded by National Science Foundation (CoPrincipal Investigator). 2012 to 2017
Foundation of Information Systems awarded by Johns Hopkins University (Principal Investigator). 2012 to 2017
Analysis of High Dimensional Complex SpatioTemporal 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 (CoPrincipal Investigator). 2011 to 2013
GEPR: Genomewide analysis of root traits awarded by National Science Foundation (CoPrincipal Investigator). 2008 to 2012
Pages
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 HighDimensional Data Using Cover Trees, Local Principal Component Analysis, and Persistent Homology. Vol. 13, Jan. 2018, pp. 93–114. Scopus, doi:10.1007/9783319895932_6. Full Text
Hughes, Michael E., et al. “Guidelines for GenomeScale 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/s130590161076z. Full Text
Perea, Jose A., et al. “SW1PerS: Sliding windows and 1persistence scoring; discovering periodicity in gene expression time series data.” Bmc Bioinformatics, vol. 16, Aug. 2015, p. 257. Epmc, doi:10.1186/s1285901506456. 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/s102080149206z. 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:10.1214/15EJS1030. 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 cellcycle progression.” Genome Biology, vol. 15, no. 9, Sept. 2014, p. 446. Epmc, doi:10.1186/s1305901404467. Full Text
Pages
Tralie, C. J., et al. “MultiScale Geometric Summaries for SimilarityBased Sensor Fusion.” Ieee Aerospace Conference Proceedings, vol. 2019March, 2019. Scopus, doi:10.1109/AERO.2019.8741399. Full Text
Tralie, C. J., et al. “Geometric crossmodal comparison of heterogeneous sensor data.” Ieee Aerospace Conference Proceedings, vol. 2018March, 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. 2018March, 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. 65.165.5. 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. “Multiscale local shape analysis and feature selection in machine learning applications.” Proceedings of the International Joint Conference on Neural Networks, vol. 2015September, 2015. Scopus, doi:10.1109/IJCNN.2015.7280428. Full Text Open Access Copy
Rouse, D., et al. “Featureaided 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 BoundedDegree 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
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Students returning to Duke University are participating in surveillance testing to help rapidly identify and isolate people who may have contracted the COVID19 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