# Paul L Bendich

- Assistant Research Professor in the Department of Mathematics
- Assistant Director of Curricular Engagement of the Information Initiative at Duke

**External address:**121 Physcis Bldg, Durham, NC 27708

**Internal office address:**Box 90320, Durham, NC 27708-0320

**Phone:**(919) 660-2811

### Research Areas and Keywords

##### Computational Mathematics

##### Signals, Images & Data

##### Topology

I work in computational topology, which for me means adapting and using tools from algebraic topology in order to study noisy and high-dimensional datasets arising from a variety of scientific applications. My thesis research involved the analysis of datasets for which the number of degrees of freedom varies across the parameter space. The main tools are local homology and intersection homology, suitably redefined in this fuzzy multi-scale context. I am also working on building connections between computational topology and various statistical data analysis algorithms, such as clustering or manifold learning, as well as building connections between computational topology and diffusion geometry.

### Selected Grants

BIGDATA: F: DKA: CSD: Topological Data Analysis and Machine-Learning with Community-Accepted Features awarded by National Science Foundation (Co-Principal Investigator). 2014 to 2018

Topological Signal Analysis for Multi-Modal Data Analysis awarded by Geometric Data Analytics, Inc. (Principal Investigator). 2016 to 2017

Tralie, CJ, Smith, A, Borggren, N, Hineman, J, Bendich, P, Zulch, P, and Harer, J. "Geometric Cross-Modal Comparison of Heterogeneous Sensor Data." *Proceedings of the 39th IEEE Aerospace Conference* (March 2018).
Open Access Copy

Bendich, P, Chin, SP, Clark, J, Desena, J, Harer, J, Munch, E, Newman, A, Porter, D, Rouse, D, Strawn, N, and Watkins, A. "Topological and statistical behavior classifiers for tracking applications." *IEEE Transactions on Aerospace and Electronic Systems* 52.6 (December 2016): 2644-2661.
Full Text

Bendich, P, Gasparovic, E, Harer, J, and Tralie, C. "Geometric Models for Musical Audio Data." *Proceedings of the 32st International Symposium on Computational Geometry (SOCG)* (June 2016).

Bendich, P, Marron, JS, Miller, E, Pieloch, A, and Skwerer, S. "Persistent homology analysis of brain artery trees." *Annals of Applied Statistics* 10.1 (2016): 198-218.
Open Access Copy

Tralie, CJ, and Bendich, P. "Cover Song Identification with Timbral Shape Sequences." *16th International Society for Music Information Retrieval (ISMIR)* (October 1, 2015): 38-44.
Open Access Copy

Bendich, P, Gasparovic, E, Harer, J, Izmailov, R, and Ness, L. "Multi-scale local shape analysis and feature selection in machine learning applications." *Proceedings of the International Joint Conference on Neural Networks* 2015-September (September 28, 2015).
Full Text Open Access Copy

Bendich, P, Cabello, S, and Edelsbrunner, H. "A point calculus for interlevel set homology." *Pattern Recognition Letters* 33.11 (August 2012): 1436-1444.
Full Text

Bendich, P, Wang, B, and Mukherjee, S. "Local homology transfer and stratification learning." *Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms* (April 30, 2012): 1355-1370.

Bendich, P, and Harer, J. "Persistent Intersection Homology." *Foundations of Computational Mathematics* 11.3 (2011): 305-336.
Full Text

Bendich, P, Galkovskyi, T, and Harer, J. "Improving homology estimates with random walks." *Inverse Problems* 27.12 (2011).
Full Text

## Pages

Bendich, P, Gasparovic, E, Harer, J, and Tralie, C. "Geometric models for musical audio data." June 1, 2016. Full Text Open Access Copy

Rouse, D, Watkins, A, Porter, D, Harer, J, Bendich, P, Strawn, N, Munch, E, Desena, J, Clarke, J, Gilbert, J, Chin, S, and Newman, A. "Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers." January 1, 2015. Full Text

For his excellent work in developing Data+ into a university model for undergraduate mentoring and research, Paul Bendich has been granted the Dean's Leadership Award. This award is given to a faculty or staff member who has made a distinctive... read more »