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Ekaterina Krymova
Ekaterina Krymova

Ekaterina Krymova

Lead Data Scientist
Academia
(Alumni)

Ekaterina received her PhD in Computer Science from Moscow Institute for Physics and Technology, Russia. Afterwards, she worked as a researcher at the Institute for Information Transmission Problems in Moscow and later as a postdoctoral researcher in the Stochastic Group at the Faculty of Mathematics at University Duisburg-Essen, Germany. She has experience with various applied projects on signal processing, predictive modelling, macroeconomic modelling and forecasting, and social network analysis. She joined the SDSC in November 2019. Her interests include machine learning, non-parametric statistical estimation, structural adaptive inference, and Bayesian modelling.

Projects

MLIBRA

In Progress
Mouse LIpid Brain Atlas
Biomedical Data Science

CHEMSPEC

In Progress
Cost-effective chemical speciation monitoring of particulate matter air pollution
Energy, Climate & Environment

PAIRED-HYDRO

In Progress
Machine learning for the components fatigue prediction in hydropower generation
Engineering

MUTIGER

In Progress
MUTations, Interactions and GEne Regulation
Biomedical Data Science

ML4FCC

In Progress
Machine Learning for the Future Circular Collider Design
Big Science Data

AURORA

In Progress
From air pollution sources to mortality
Biomedical Data Science
Energy, Climate & Environment

PolyNet

Completed
Exploring disease trajectories and outcome prediction using novel methods in network analysis and machine learning
Biomedical Data Science

COVID-19

Completed
Epidemic Forecasting
Biomedical Data Science
Big Science Data
Digital Administration

PACMAN LHC

Completed
Particle Accelerators and Machine Learning
Big Science Data

EconMultiplex

Completed
Multiplex Networks in International Trade
Digital Administration

Publications

Vagnoni, E.; Muser, T.; Seydoux, M.; Morabito, A.; Krymova, E. "On the modelling of the fatigue-induced damage in Francis turbines start-up sequences" IOP Conference Series: Earth and Environmental Science 1411 1.0 012043 2024 View publication
Di Croce, D.; Giovannozzi, M.; Krymova, E.; Pieloni, T.; Redaelli, S.; Seidel, M.; Tomás, R.; Van Der Veken, F. "Optimizing dynamic aperture studies with active learning" Journal of Instrumentation 19 4.0 P04004 2024 View publication
Grover, A.; Zhang, L.; Muser, T.; Häfliger, S.; Wang, M.; Yates, J.; Van Allen, E. M.; Theis, F. J.; Ibarra, I. L.; Krymova, E.; et al. "UniversalEPI: a generalized attention-based deep ensemble model to accurately predict enhancer-promoter interactions across diverse cell types and conditions" Preprint 2024 View publication
Di Croce, D.; Giovannozzi, M.; Krymova, E.; Pieloni, T.; Seidel, M.; Van der Veken, F. F. "Optimizing Beam Dynamics in LHC with Active Deep Learning" HB2023 - Proceedings 2023 View publication
Brockhaus, E. K.; Wolffram, D.; Stadler, T.; Osthege, M.; Mitra, T.; Littek, J. M.; Krymova, E.; Klesen, A. J.; Huisman, J. S.; Heyder, S.; et al. "Why are different estimates of the effective reproductive number so different? A case study on COVID-19 in Germany" PLOS Computational Biology 19 11 e1011653 2023 View publication
Sherratt, K.; Gruson, H.; Grah, R.; Johnson, H.; Niehus, R.; Prasse, B.; Sandmann, F.; Deuschel, J.; Wolffram, D.; Abbott, S.; et al. "Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations" eLife 12 e81916 2023 View publication
Krymova, E.; Obozinski, G.; Schenk, M.; Coyle, L.; Pieloni, T. "Data-driven modeling of beam loss in the LHC" Preprint 2022 View publication
Krymova, E.; Obozinski, G.; Schenk, M.; Coyle, L. T.; Pieloni, T. "Data-driven modeling of beam loss in the LHC" Available at: https://zenodo.org/record/7305102 2022 View publication
Cramer, E. Y.; Huang, Y.; Wang, Y.; Ray, E. L.; Cornell, M.; Bracher, J.; Brennen, A.; Rivadeneira, A. J. C.; Gerding, A.; House, K.; et al. "The United States COVID-19 Forecast Hub dataset" Scientific Data 9 1 462 2022 View publication
Bracher, J.; Wolffram, D.; Deuschel, J.; Görgen, K.; Ketterer, J. L.; Ullrich, A.; Abbott, S.; Barbarossa, M. V.; Bertsimas, D.; Bhatia, S.; et al. "National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021" Communications Medicine 2 1 136 2022 View publication
Krymova, E.; Béjar, B.; Thanou, D.; Sun, T.; Manetti, E.; Lee, G.; Namigai, K.; Choirat, C.; Flahault, A.; Obozinski, G. "Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide" Proceedings of the National Academy of Sciences 119 32.0 e2112656119 2022 View publication
Schenk, M.; Coyle, L.; Giovannozzi, M.; Krymova, E.; Mereghetti, A.; Obozinski, G.; Pieloni, T. "Modeling Particle Stability Plots for Accelerator Optimization Using Adaptive Sampling" Proceedings of the 12th International Particle Accelerator Conference IPAC2021 2021 View publication
Coyle, L.; Blanc, F.; Buffat, X.; Krymova, E.; Obozinski, G.; Pieloni, T.; Schenk, M.; Solfaroli Camillocci, M.; Wenninger, J. "Detection and Classification of Collective Beam Behaviour in the LHC" Proceedings of the 12th International Particle Accelerator Conference IPAC2021 2021 View publication
Schenk, M.; Coyle, L.; Giovannozzi, M.; Krymova, E.; Mereghetti, A.; Obozinski, G.; Pieloni, T. "Modeling Particle Stability Plots for Accelerator Optimization Using Adaptive Sampling" Proceedings of the 12th International Particle Accelerator Conference IPAC2021 4 pages, 15.019 MB 2021 View publication
Bracher, J.; Wolffram, D.; Deuschel, J.; Görgen, K.; Ketterer, J.; Ullrich, A.; Abbott, S.; Barbarossa, M.; Bertsimas, D.; Bhatia, S.; et al. "Short-term forecasting of COVID-19 in Germany and Poland during the second wave – a preregistered study" Preprint 2020 View publication

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