Vasileios Maroulas

Teaching Short Bio Personal Links

Contact Info

Office:  Ayres Hall 202

Phone:  865-974-4302


Department of Mathematics
University of Tennessee
202 Ayres Hall
1403 Circle Drive
Knoxville, TN 37996-1320

Henri Poincare

It is through science that we prove, but through intuition that we discover.

Publications  (brief sample)

Personal Research Statement:

     My research portfolio is by nature interdisciplinary and focuses on computational mathematics and statistics with applications of their theory in several engineering and scientific problems. Precisely, I work in the area of computational Bayesian filtering, large deviations, stochastic optimization and phylogentics. I also develop mathematical data science methods using statistical learning, stochastic modeling, topology and geometry. The foci of applications are big data problems related to national security and defense, e.g. multi- object trajectory estimation, biology at the cellular level, e.g. intracellular movements, material science, e.g. quantifying uncertainty related to high entropy alloys (HEAs) materials, physiological, e.g. understanding of kidney functions, and clinical, e.g. analyzing kidney exchange graphs.

        I am deeply grateful and thankful to the AFOSR, ARL, ARO, DOE, NSF, the Simons Foundation, and the Leverhulme Trust Fellowship in the UK, for funding my research.

       Below is a very short sample of my research. Please look at my resume or Google Scholar for my publications.

A.    Journal Papers

1.     A. Budhiraja, P. Dupuis and V. Maroulas. Large deviations for infinite dimensional stochastic dynamical systems, Annals of Probability, 36(4), (2008), 1390-1420.

2.     A. Budhiraja, P. Dupuis and V. Maroulas. Large deviations for stochastic flows of diffeomorphisms. Bernoulli, 16(1), 234-256, 2010.

3.     A. Budhiraja, P. Dupuis and V. Maroulas. Variational representations for continuous time processes. Annales de l Institut de Henri Poincare, 47(3), pp. 725-747, 2011.

4.   V. Maroulas and P. Stinis. Improved particle filters for multi-target tracking. Journal of Computational Physics, 231(2), pp.602-611, 2012.

5.     V. Maroulas and J. Xiong. Large deviations for optimal filtering with fractional Brownian motion. Stochastic Processes and their Applications, 123(6), pp. 2340-2352, 2013.

6.  D.-C. Jhwueng  and V. Maroulas. Phylogenetic Ornestein-Uhlenbeck regression curves. Statistics & Probability Letters, 89, pp. 110-117, 2014.

7.   V. Maroulas and A. Nebenfuhr. Tracking rapid intracellular movements: a Bayesian random set approach. Annals of Applied Statistics, 9(2), pp. 926-949, 2015.

8. G. Ren, V. Maroulas and I.D. Schizas. Distributed Sensors-Targets Spatiotemporal Association and Tracking.  IEEE Transactions on Aerospace and Electronic Systems, (51)  4, pp. 2570-2589 2015.

9. I. Sgouralis, V. Maroulas and A. Layton. Transfer function analysis of dynamic blood flow control in the rat kidney, Bulletin of Mathematical Biology, 78(5): 923-60, 2016

10. J. Mike, C. Sumrall, V. Maroulas and F. Schwartz. Non-landmark classification in paleobiology: computational geometry as a tool for species discrimination. Paleobiology, 1-11, 2016.

11. I. Sgouralis, A. Nebenfuhr, and V. Maroulas. A Bayesian topological framework for the identification and reconstruction of subcellular motion. SIAM Journal on Imaging Sciences, 10(2), pp. 871-899, 2017.

12.  E. Evangelou and V. Maroulas. Sequential Empirical Bayes method for filtering dynamic spatiotemporal processes. Spatial Statistics, 21(Part A), pp. 114-129, 2017.

13. F. Bao and V. Maroulas. Adaptive Meshfree Backward SDE Filter. SIAM Scientific Computing 39(6), A2664-2683, 2017.

14. K. Kang, V. Maroulas, I. Schizas and F. Bao. Improved distributed particle filters for tracking in wireless sensor network. Computational Statistics and Data Analysis, (117), pp. 90-108, 2018.

B.    Code

    J. Mike and V. Maroulas. Combinatorial Hodge theory for equitable kidney paired donation. Submitted 2016. For the code of the associated paper click here.

C.    Conference Papers (peer-reviewed)

1. A. Aduroja, I. D. Schizas and V. Maroulas. Distributed principal component analysis in sensor networks. IEEE Proceedings of ICASSP, pp. 5850-5854, 2013.

2.  K. Kang and V. Maroulas. Drift homotopy methods for a non-Gaussian filter. The Proceedings of Data Fusion, pp. 1088-1094, 2013.

3. V. Maroulas, K. Kang, I. D. Schizas and M. W. Berry. A Learning Drift Homotopy Particle Filter, The Proceedings of Data Fusion, pp. 1930-1937, 2015.

4. A. Marchese and V. Maroulas. Topological learning for acoustic signal identification. The Proceedings of Data Fusion. pp. 1377-1381, 2016.

5. A. Marchese, V. Maroulas and J. Mike. K-Means clustering on the space of persistence diagrams. Wavelets and Sparsity XVII, SPIE Conference Proceedings, 2017.

D.    Other Contributions (peer-reviewed)

V. Maroulas, Probability Matrices. Encyclopedia of Social Network
        Analysis and Mining,
pp. 1416-1418, Springer NY, 2014.

E.  PhD Thesis

Small noise Large Deviations for Infinite Dimensional Stochastic Dynamical Systems, University of North Carolina at Chapel Hill, May 2008. [pdf]