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
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.

Education & Training
  • Ph.D., University of California at 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

An Adaptive Pipeline from Scientific Data to Models awarded by Defense Advanced Research Projects Agency (Principal Investigator). 2017 to 2020

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 (Principal Investigator). 2016 to 2018

EMSW21-RTG: Geometric, Topological awarded by National Science Foundation (Principal Investigator). 2011 to 2018

ATD: Online Multiscale Algorithms for Geometric Density Estimation in High-Dimensions and Persistent Homology of Data fo awarded by National Science Foundation (Co-Principal Investigator). 2012 to 2017

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 awarded by Air Force Office of Scientific Research (Principal Investigator). 2010 to 2015

Pages

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

Tralie, C. J., et al. “Multi-Scale Geometric Summaries for Similarity-Based Sensor Fusion.” Ieee Aerospace Conference Proceedings, vol. 2019-March, Mar. 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, June 2018, pp. 1–10. Scopus, doi:10.1109/AERO.2018.8396789. Full Text Open Access Copy

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. Epmc, doi:10.1186/s13059-016-1076-z. Full Text

Bendich, P., et al. “Geometric Models for Musical Audio Data.” Proceedings of the 32st International Symposium on Computational Geometry (Socg), June 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, Sept. 2015. Scopus, doi:10.1109/IJCNN.2015.7280428. Full Text Open Access Copy

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. 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

Pages

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

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

Former Graduate Students

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