Ekaterina Krymova
A5029889274- Impact of AI and Big Data on Business and Society
- COVID-19, Geopolitics, Technology, Migration
- Regional Socio-Economic Development Trends
- COVID-19 epidemiological studies
- Data-Driven Disease Surveillance
- Market Dynamics and Volatility
- Particle Accelerators and Free-Electron Lasers
- Speech and Audio Processing
- Superconducting Materials and Applications
- Particle Detector Development and Performance
- COVID-19 Pandemic Impacts
- Blind Source Separation Techniques
- Stochastic Gradient Optimization Techniques
- Sparse and Compressive Sensing Techniques
- Advanced Adaptive Filtering Techniques
- Advanced Bandit Algorithms Research
- Aquatic and Environmental Studies
- SARS-CoV-2 and COVID-19 Research
- Optimization and Search Problems
- RNA and protein synthesis mechanisms
- Flow Measurement and Analysis
- COVID-19 Digital Contact Tracing
- Approximation Theory and Sequence Spaces
- Complex Systems and Time Series Analysis
- Water Systems and Optimization
Swiss Data Science Center
2020-2025
ETH Zurich
2020-2025
École Polytechnique Fédérale de Lausanne
2020-2025
Board of the Swiss Federal Institutes of Technology
2022-2023
University of Duisburg-Essen
2017-2019
Institute for Information Transmission Problems
2013-2018
Essen University Hospital
2018
Moscow Institute of Physics and Technology
2015
Computing Center
2011
Russian Academy of Sciences
2011
Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields recent insights epidemiology, one maximise the predictive performance such if multiple models are combined into an ensemble. Here, we report ensembles predicting COVID-19 cases deaths across Europe between 08 March 2021 07 2022.
Abstract Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve reliability of outputs. Here we report insights from ten weeks collaborative short-term forecasting in Germany Poland (12 October–19 December 2020). The study period covers onset second wave both countries, with tightening non-pharmaceutical interventions (NPIs) subsequently a decay (Poland) or plateau renewed...
Abstract As the global shift towards renewable energy accelerates, achieving stability in power systems is crucial. Hydropower accounts for approximately 17% of produced worldwide, and with its capacity active reactive regulation, well-suited to provide necessary ancillary services. However, as demand these services rises, hydropower must adapt handle rapid dynamic changes off-design conditions. Fatigue damage hydraulic machines, driven by fluctuating loads varying mechanical stresses,...
Yield of protein per translated mRNA may vary by four orders magnitude. Many studies analyzed the influence features on translation yield. However, a detailed understanding how sequence determines its propensity to be is still missing. Here, we constructed set reporter plasmid libraries encoding CER fluorescent preceded randomized 5΄ untranslated regions (5΄-UTR) and Red (RFP) used as an internal control. Each library was transformed into Escherchia coli cells, separated efficiency cell...
During the COVID-19 pandemic there has been a strong interest in forecasts of short-term development epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions confirmed cases and deaths from Germany Poland for period January through April 2021.
Abstract Fine-grained prediction of chromatin accessibility from DNA sequence is a foundational step in modeling gene expression changes resulting variants. Yet, few methods operate at the resolution necessary to capture subtle effects single-nucleotide changes. Furthermore, it remains unclear which architectural components—such as residual connections, normalization strategies, or attention mechanisms—drive performance these high-resolution predictions. To address knowledge gaps, we...
Since the beginning of COVID-19 pandemic, many dashboards have emerged as useful tools to monitor its evolution, inform public, and assist governments in decision-making. Here, we present a globally applicable method, integrated daily updated dashboard that provides an estimate trend evolution number cases deaths from reported data more than 200 countries territories, well 7-d forecasts. One significant difficulties managing quickly propagating epidemic is details dynamic needed forecast are...
Abstract We report insights from ten weeks of collaborative COVID-19 forecasting for Germany and Poland (12 October – 19 December 2020). The study period covers the onset second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) subsequently a decay (Poland) or plateau renewed increase (Germany) reported cases. Thirteen independent teams provided probabilistic real-time forecasts cases deaths. These were lead times one to four weeks, evaluation focused on one-...
The effective reproductive number Rt has taken a central role in the scientific, political, and public discussion during COVID-19 pandemic, with numerous real-time estimates of this quantity routinely published. Disagreement between can be substantial may lead to confusion among decision-makers general public. In work, we compare different national-level Germany 2020 2021. We consider agreement from same method but published at time points (within-method agreement) as well retrospective...
Abstract Background Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields recent insights epidemiology, one maximise the predictive performance such if multiple models are combined into an ensemble. Here we report ensembles predicting COVID-19 cases deaths across Europe between 08 March 2021 07 2022. Methods We used open-source tools develop a public European Forecast Hub. invited groups...
The main goal in this paper is to propose a new approach deriving oracle inequalities related the exponential weighting method. focuses on recovering an unknown vector from noisy data with help of family ordered smoothers [12]. estimators withing are aggregated using method and aim control risk estimate. Based natural probabilistic properties unbiased estimate, we derive for mean square show that permits improve Kneip's inequality.
Abstract Background During the COVID-19 pandemic there has been a strong interest in forecasts of short-term development epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions confirmed cases and deaths from Germany Poland for period January through April 2021. Methods We Poland. These were issued by 15 different forecasting models, run independent research teams. Moreover, performance combined ensemble forecasts. Evaluation is...
Spectral complexity reduction can be used to emphasize the leading voice or melody and attenuate competing accompaniment of music pieces. This method is known facilitate perception in cochlear implant (CI) users as spectrally less complex signals are perceived being more pleasant. In this paper we investigate a obtain reduced-rank approximation for desired that extends established projection subspace tracking methods (PAST, CPAST) with an additional sparsity constraint. We evaluate our...
We study the problem of nonparametric estimation risk-neutral densities from options data. The underlying statistical is known to be ill-posed and needs regularized. propose a novel regularized empirical sieve approach for which relies on notion minimal martingale entropy measure. proposed can used estimate so-called pricing kernels play an important role in assessing risk aversion over equity returns. asymptotic properties resulting are analyzed its performance illustrated.