Prof. Dr. Illia Horenko

Home University:
L’Università della Svizzera italiana (USI)
Institute of Computational Science
Faculty of Informatics

Via Giuseppe Buffi 13
6900 Lugano
Switzerland

+41 58 666 4123
illia.horenko-at-usi.ch
Homepage

 

A central scientific issue in the work programme of CRC1114 recurring in several of the individual projects is the unbiased characterization of observation, measurement, and simulation data in multiscale systems. The size of the data emerging in the CRC’s application domains, e.g., in molecular dynamics and the geosciences, together with the multiscale character of the underlying systems necessitate not only the deployment of High-Performance-ready data analysis tools, but also call for overcoming the usual parametric assumptions of common statistical tools, such as stationarity, Gaussianity or linearity.

The Mercator Fellow will offer his expertise and experience with multiscale data analysis problems in the natural sciences accumulated by him and his group at USI Lugano; he will contribute with a direct possibility to use Europe’s most powerful supercomputer “Piz Daint” (place 3 in the TOP 500) at CSCS Lugano for data analysis problems in CRC1114; and he will provide access to and user advice for the high-performance multiscale data analysis methods developed in recent years under his guidance. The latter include a Finite Element Framework for nonparametric denoising and nonstationary model inference, that are scalable to be used even on emerging supercomputing architectures involving Graphical Processing Units. The role of the Mercator Fellow in the CRC is thus twofold: He will (i) support the individual projects in addressing questions related to the analysis of multiscale data, and (ii) develop new multiscale data analysis tools and software applications, motivated by the problems and questions emerging in CRC.

Project publications (Mercator Fellow)

27.4.2021. Number of items: 12.

2021

Rodrigues, D.R. and Everschor-Sitte, K. and Gerber, S. and Horenko, I. (2021) A deeper look into natural sciences with physics-based and data-driven measures. iSCIENCE, 24 (3). pp. 1-13. ISSN 102171

2020

Horenko, I. (2020) On a Scalable Entropic Breaching of the Overtting Barrier for Small Data Problems in Machine Learning. Neural Computation, 32 (8). pp. 1563-1579.

Gerber, S. and Pospisil, L. and Navandar, M. and Horenko, I. (2020) Low-cost scalable discretization, prediction and feature selection for complex systems. Science Advances, 6 (5).

2019

Rosenau, M. and Horenko, I. and Corbi, F. and Rudolf, M. and Kornhuber, R. and Oncken, O. (2019) Synchronization of great subduction megathrust earthquakes: Insights from scale model analysis. Journal of Geophysical Research: Solid Earth, 124 (4). pp. 3646-3661. ISSN 2169-9356

2018

Marchenko, A. and Gagliardini, P. and Horenko, I. (2018) Toward a computationally-tractable maximum entropy principle for non-stationary financial time series. SIAM Journal of Financial Mathematics, 9 (4). pp. 1249-1285. ISSN 1945-497X

Gerber, S. and Olsson, S. and Noé, F. and Horenko, I. (2018) A scalable approach to the computation of invariant measures for high-dimensional Markovian systems. Scientific Reports, 8 (1796). ISSN 2045-2322

Pospisil, L. and Gagliardini, P. and Sawyer, W. and Horenko, I. (2018) On a scalable nonparametric denoising of time series signals. Communications in Applied Mathematics and Computational Science, 13 (1). pp. 107-138.

2017

Gerber, S. and Horenko, I. (2017) Toward a direct and scalable identification of reduced models for categorical processes. Proceedings of the National Academy of Sciences, 114 (19). pp. 4863-4868.

O'Kane, T.J. and Monselesan, D.P. and Risbey, J.S. and Horenko, I. and Franzke, Ch.L.E. (2017) On memory, dimension, and atmospheric teleconnection patterns. Math. Clim. Weather Forecast, 3 (1). pp. 1-27.

Horenko, I. and Gerber, S. and O'Kane, T.J. and Risbey, J.S. and Monselesan, D.P. (2017) On inference and validation of causality relations in climate teleconnections. In: Nonlinear and Stochastic Climate Dynamics. Cambridge University Press, pp. 184-208. ISBN 9781107118140

2015

Horenko, I. and Gerber, S. (2015) Improving clustering by imposing network information. Science Advances, 1 (7). ISSN 2375-2548

O’Kane, T.J. and Risbey, J.S. and Monselesan, D.P. and Horenko, I. and Franzke, Ch.L.E. (2015) On the dynamics of persistent states and their secular trends in the waveguides of the Southern Hemisphere troposphere. Climate Dynamics . ISSN Print: 0930-7575, Online: 1432-0894