Eniko Székely

Sr. Data Scientist

Alumni

(Alumni)

Eniko joined SDSC as a senior data scientist in September 2017. Previously, she was a postdoctoral researcher at the Courant Institute of Mathematical Sciences, New York University, working on machine learning for dynamical systems and climate science. She obtained her PhD in Computer Science from the University of Geneva, Switzerland (2011), her MSc from Telecom Bretagne, France (2006) and her BSc from the University of Timisoara, Romania (2005). Broadly she is interested in machine learning for nonlinear phenomena and high-dimensional data, and more recently she has been working on using machine learning approaches to advance our understanding of the climate.

Projects

DeepCloud

Completed

A data-driven sub-grid parametrization for complex terrain

Academia

EXPECT

Completed

EXtending the PrEdiCTability of the Atmosphere over Europe

Academia

DASH

Completed

DAta Science-informed attribution of changes in the Hydrological cycle

Academia

Publications

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De Fondeville, R.; Wu, Z.; Székely, E.; Obozinski, G.; Domeisen, D. I. V. "Improved extended-range prediction of persistent stratospheric perturbations using machine learning" Weather and Climate Dynamics 4 2 287-307 2023 View publication 

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Bertoli, G.; Schemm, S.; Ozdemir, F.; Perez Cruz, F.; Szekely, E. "Building a physics-constrained, fast and stable machine learning-based radiation emulator" EGU General Assembly Conference Abstracts 2023 View publication 

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Wu, Z.; Jiménez-Esteve, B.; De Fondeville, R.; Székely, E.; Obozinski, G.; Ball, W. T.; Domeisen, D. I. V. "Emergence of representative signals for sudden stratospheric warmings beyond current predictable lead times" Weather and Climate Dynamics 2 3 841-865 2021 View publication 

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Sippel, S.; Meinshausen, N.; Székely, E.; Fischer, E.; Pendergrass, A. G.; Lehner, F.; Knutti, R. "Robust detection of forced warming in the presence of potentially large climate variability" Science Advances 7 43 eabh4429 2021 View publication 

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Sippel, S.; Meinshausen, N.; Fischer, E. M.; Székely, E.; Knutti, R. "Climate change now detectable from any single day of weather at global scale" Nature Climate Change 10 1 35-41 2020 View publication 

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Das, S.; Giannakis, D.; Székely, E. "An information-geometric approach to feature extraction and moment reconstruction in dynamical systems" Preprint 2020 View publication 

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Székely, E.; Sippel, S.; Knutti, R.; Obozinski, G.; Meinshausen, N. "A direct approach to detection and attribution of climate change" Proceedings of the 9th International Conference on Climate Informatics 2019 View publication 

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Székely, E.; Sippel, S.; Knutti, R.; Obozinski, G.; Meinshausen, N. "A direct approach to detection and attribution of climate change" Proceedings of the 9th International Workshop on Climate Informatics: CI2019 2019 View publication 

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Wüest, R. O.; Zimmermann, N. E.; Zurell, D.; Alexander, J. M.; Fritz, S. A.; Hof, C.; Kreft, H.; Normand, S.; Cabral, J. S.; Szekely, E.; et al. "Macroecology in the age of Big Data – Where to go from here?" Journal of Biogeography 47 1-12 2019 View publication 

Mentioned in

September 27, 2019

"Climate is what you expect, weather is what you get"

While we know for certain that global temperature is rising, other questions still remain surrounded by uncertainty. How strongly will the Earth’s temperature respond to increasing CO2 levels? What changes will happen on regional scales and how strong will they be?

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