Curriculum Vitae 
Primoz Skraba Affiliation:

I am a researcher in the Artificial Intelligence Laboratory. I also hold positions at the University of Primorska and University of Nova Gorica. My research is broadly related to data analysis with an emphasis on topological data analaysis as an application of applied and computational topology. I generally have an interest in both theory and applications. On the theory side, topics of interest are the stability and foundations of persistent (co)homology as well as more recently stochastic topology (the topology of random spaces). On the applications side, my interests are broadly data analysis tools. This includes data analysis, machine learning as well as many other statistical tools. Other areas of interest include visualization and geometric methods. A long time ago I worked in sensor networks and occasionally some new work may pop up. You can find a partial list of my papers below with links, with most of them available on arXiv. For a complete list see my CV. 
P. Skraba, G. Thoppe, D. Yogeshwaran,
Randomly Weighted dComplexes: Minimal Spanning Acycles and Persistence Diagrams,
submitted to Random Structures and Algorithms
D. Govc, P. Skraba,
An Approximate Nerve Theorem,
submitted to the Foundations of Computational Mathematics
L. Stopar, P. Skraba, M. Grobelnik, D. Mladenic,
StreamStory: Exploring Multivariate Time Series on Multiple Scales,
submitted to IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017)
Website
B. Kazic, J. Rupnik, P. Skraba, L. Bradesko, D. Mladenic,
Predicting Usersâ€™ Mobility Using Monte Carlo Simulations,
submitted to IEEE Access
O. Bobrowski, M. Kahle, and P. Skraba,
Maximally Persistent Cycles in Random Geometric Complexes,
Accepted to the Annals of Applied Probability,
G. Kudryavtseva and P. Skraba,
The principal bundles over an inverse semigroup,
Semigroup Forum 2016, pp. 120
M. Kerber, D. Sheehy, P. Skraba,
Persistent Homology and Nested Dissection,
Annual ACMSIAM Symposium on Discrete Algorithms,
SIAM, 2016,
Arlington, Virginia, USA.
C. Fortuna, E. De Poorter, P. Skraba, I. Moerman,
Data Driven Wireless Network Design: a Multilevel Modeling Approach ,
Wireless Personal Communications 88.1 (2016): 6377.
P. Skraba, P. Rosen, B. Wang, G. Chen, V. Pasucci.
Critical Point Cancellation in 3D Vector Fields: Robustness and Discussion,
IEEE Pacific Visualization 2016 and in IEEE Transactions in Computer Graphics and Visualization
vol. 22, no. 6, p. 16831693
Best Paper Award
J. Rupnik, A. Muhic, G. Leban, P. Skraba, B. Fortuna, M. Grobelnik,
News Across Languages  CrossLingual Document: Similarity and Event Tracking,
JAIR: Special Track on Crosslanguage Algorithms and Applications
P. Skraba and M. VejdemoJohansson,
Topology, Big Data and Optimization,
Big Data Optimization: Recent Developments and Challenges
Volume 18 of the series Studies in Big Data pp 147176, Springer.
M. VejdemoJohansson, F. Pokorny, P. Skraba, D. Kragic,
Cohomological learning of periodic motion,
Applicable algebra in engineering, communication and computing, 2015,
vol. 26, no. 1/2, p. 526.
Video
P. Skraba, B. Wang, G. Chen, P. Rosen,
Robustnessbased simplification of 2D steady and unsteady vector fields,
IEEE Trans. on visualization and computer graphics, 2015,
vol. 21, issue 8, pp. 930944
M. Mole, L. Wang, K. Bergant, W. Eichinger, S. Stanic, P. Skraba,
Lidar measurements of Bora wind effects on aerosol loading,
International Symposium on Atmospheric Light Scattering and Remote Sensing (ISALSaRS'15),
June 15, 2015
P. Skraba, B. Wang, G. Chen, P Rosen,
2D vector field simplification based on robustness,
7th Pacific Visualization Symposium,PacificVis 2014
March 47, 2014, Yokohama, Japan
Best Paper Award
P. Skraba, B. Wang,
Approximating local homology from samples,
Proceedings of the TwentyFifth Annual ACMSIAM Symposium on Discrete Algorithms,
January 57, 2014, Portland, Oregon, USA, p. 174192.
P. Skraba, B. Wang,
Interpreting feature tracking through the lens of robustness,
Topological methods in data analysis and visualization III: theory, algorithms applications,
(Mathematics and visualization), Springer, 2014, p. 1937
F. Chazal, L. Guibas, S. Oudot, P. Skraba,
PersistenceBased Clustering in Riemannian Manifolds,
Journal of the ACM,
vol. 60, no. 6, Article 10
Also appeared in the Sympoisum of Computationa Geometry 2011
B. Wang, P. Rosen, P. Skraba, H. Bhatia, V. Pasucci,
Visualizing robustness of critical points for 2D timevarying vector fields,
Proceedings of the 15th EuroVis 2013,The European Conference on Visualization,
June 1721, 2013, Leipzig, Germany,
(Computer graphics forum, vol. 32, no. 3, pt. 2 pp. 221230)
F. Chazal, A. Patel, P. Skraba,
Computing Robustness of Roots,
Applied Mathematical Letters
2012 vol. 25, no. 11, pp. 17251728
N. Milosavljevic, D. Morozov, P. Skraba,
Computing ZigZag Persistence in Matrix Multiplication Time,
Symposium of Computational Geometry 2011,
Paris, France
F. Chazal, L. Guibas, S. Y. Oudot, P. Skraba,
Analysis of Scalar Fields over Point Cloud Data,
Discrete and Computational Geometry 2011
Also appeared in the Symposium on Discrete Algorithms 2008
P. Skraba, M. Ovsjanikov, F. Chazal, L. Guibas,
Persistence Based Segmentation of Deformable Shapes,
NORDIACVPR Workshop on Deformable Shape Analysis 2010,
San Francisco, CA, USA,
Best Paper Award
A. Motskin, T. Roughgarden, P. Skraba, and L. Guibas,
Lightweight Coloring and Desynchronization for Networks,
INFOCOMM 2009
P. Skraba, Topology in Sensor Networks,
Ph.D. Dissertation,
Stanford University,
December 2008
P. Skraba and L. Guibas,
Energy Efficient Intrusion Detection in Camera Sensor Networks,
DCOSS 2007,
Santa Fe, New Mexico
P. Skraba, Q. Fang, A. Nguyen, L. Guibas,
Sweeps over Sensor Networks,
IPSN 2006