Omer Bobrowski

I am no longer at Duke. I moved to Technion Israel Institute of Technology.
This is my new website:


I am a Visiting Assistant Professor in the Mathematics Department at Duke University.

Contact Information

Office: 222 Physics Building

Phone: (919) 660-2878

Email: olmlelrl@lmlaltlhl.ldlulklel.leldlu

Department of Mathematics

Duke University

Durham, NC 27708

Research Interests

       Stochastic topology. More specifically - algebraic topology of random fields and complexes.

       Statistical theory for topological data analysis (TDA).

       Statistical models and applications for TDA.

       Probability and stochastic processes.


       Maximally Persistent Cycles in Random Geometric Complexes
O. Bobrowski, M. Kahle, and P. Skraba
Submitted, arXiv:1509.04347, 2015.

       On the Vanishing of Homology in Random Čech Complexes
O. Bobrowski, and S. Weinberger
Submitted, arXiv:1507.06945, 2015.

       The Topology of Probability Distributions on Manifolds
O. Bobrowski, and S. Mukherjee
Probability Theory and Related Fields 161 (3-4): 651-686, 2015

       Topology of Random Geometric Complexes: A Survey
O. Bobrowski, M. Kahle
To appear in: Topology in Statistical Inference, the Proceedings of Symposia in Applied Mathematics, arXiv:1409.4734, 2014.

       Topological Consistency via Kernel Estimation
O. Bobrowski, S. Mukherjee and J. Taylor
To Appear in Bernoulli, arXiv:1407.5272, 2014.

       Crackle: The Homology of Noise
R.J. Adler, O. Bobrowski, and S. Weinberger
Discrete and Computational Geometry 52 (4): 680-704, 2014

       Distance Functions, Critical Points, and the Topology of Random Cech Complexes
O. Bobrowski, R.J. Adler
Homology, Homotopy and Applications 16 (2): 311-344, 2014

       Euler Integration of Gaussian Random Fields and Persistent Homology
O. Bobrowski, M.S. Borman
Journal of Topology and Analysis, 4(1), 2012.

       Persistent Homology for Random Fields and Complexes
R.J. Adler, O. Bobrowski, M.S. Borman, E. Subag and S. Weinberger
Borrowing Strength: Theory Powering Applications, A festschrift for Lawrence D. Brown. IMS Collections Vol. 6, 2010.

       Bayesian Filtering in Spiking Neural Networks: Noise, Adaptation and Multisensory Integration
O. Bobrowski, R. Meir and Y. C. Eldar
Neural Computation 21(5), 2009.

PDF, online appendix.

       A Neural Network Implementing Optimal State Estimation Based on Dynamic Spike Train Decoding
O. Bobrowski, R. Meir, S. Shoham and Y. C. Eldar

Neural Information Processing Systems (NIPS 2007).


       PhD Thesis: Algebraic Topology of Random Fields and Complexes
Advisor: Prof. Robert J. Adler

       MSc Thesis: Real Time Spike Train Decoding by Neural Networks
Advisors: Prof. Ron Meir and Prof. Yonina C. Eldar


Fall 2015:
MATH/STAT 690 - Topics in Probability
STAT 130 - Probability and Statistics in Engineering

Fall 2014/2013/2013:
MATH 212 - Mutlivariate Calculus

A Neat (?) Simulation

Move your mouse to change angles, and you can click the following:

z/x - zoom in/out

left/right - change size

up/down - speed

f/g - fluctuations (more/less)

r - start over

p - pause (on/off)

s - show a slice (on/off)

0-9 - take a screenshot