Publications by Guillaume Romain Obozinski

STEEL-3dPointClouds: dataset supporting quantification of residual life and reusability of steel beam-columns

Dimitrios Lignos, Isinsu Katircioglu, Nenad Bijelic, Guillaume Romain Obozinski

This paper presents STEEL-3dPointClouds, a dataset of deformed steel beam-columns obtained using high-fidelity physics-based numerical simulations. These simulations trace the inelastic deformations of hot-rolled wide-flange steel beam-columns under differ ...

Springer Science and Business Media LLC2025

Real-time estimates of Swiss electricity savings using streamed smart meter data

Roberto Castello, Fabian Heymann, Guillaume Romain Obozinski

The gas crisis of 2022 put pressure on electricity prices in Europe, prompting the Swiss government to launch a national energy-saving campaign. To effectively quantify potential savings and guide timely decision-making, this campaign called for rigorous n ...

2025

From STEM-EDXS data to phase separation and quantification using physics-guided NMF

Cécile Hébert, Duncan Thomas Lindsay Alexander, Guillaume Romain Obozinski, Nathanaël Perraudin

We present the development of a new algorithm which combines state-of-the-art energy-dispersive x-ray (EDX) spectroscopy theory and a suitable machine learning formulation for the hyperspectral unmixing of scanning transmission electron microscope EDX spec ...

2024

Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains

Guillaume Romain Obozinski

Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale ...

San Francisco2024

espm: A Python library for the simulation of STEM-EDXS datasets

Cécile Hébert, Duncan Thomas Lindsay Alexander, Hui Chen, Guillaume Romain Obozinski, Nathanaël Perraudin

We present two open-source Python packages: "electron spectro-microscopy"(espm) and "electron microscopy tables"(emtables). The espm software enables the simulation of scanning transmission electron microscopy energy-dispersive X-ray spectroscopy datacubes ...

ELSEVIER2023

Improved extended-range prediction of persistent stratospheric perturbations using machine learning

Guillaume Romain Obozinski, Raphaël Gérard Théodore Michel Marie de Deloÿe et Fourcade de Fondeville

On average every 2 years, the stratospheric polar vortex exhibits extreme perturbations known as sudden stratospheric warmings (SSWs). The impact of these events is not limited to the stratosphere: but they can also influence the weather at the surface of ...

Copernicus Gesellschaft Mbh2023

Harnessing data science to improve molecular structure elucidation from tandem mass spectrometry

Guillaume Romain Obozinski, Marco Volpi, Fernando Perez Cruz

Compound structural identification for non-targeted screening of organic molecules in complex mixtures is commonly carried out using liquid chromatography coupled to tandem mass spectrometry (UHPLC-HRMS/MS and related techniques). Instrumental developments ...

2023

Identification of polypharmacy patterns in new-users of metformin using the Apriori algorithm: A novel framework for investigating concomitant drug utilization through association rule mining

Guillaume Romain Obozinski

Purpose: With increased concomitant chronic diseases in type 2 diabetes mellitus (T2DM), the use of multiple drugs increases as well as the risk of drug-drug interac-tions (DDI) and adverse drug reactions (ADR). Nevertheless, how medication patterns vary i ...

2023

Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide

Benjamin Bejar Haro, Ekaterina Krymova, Ntorina Thanou, Guillaume Romain Obozinski, Christine Choirat

Since the beginning of the COVID-19 pandemic, many dashboards have emerged as useful tools to monitor its evolution, inform the public, and assist governments in decision-making. Here, we present a globally applicable method, integrated in a daily updated ...

National Academy of Sciences2022

Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland

Guillaume Romain Obozinski, Fernando Perez Cruz

Even today, the assessment of avalanche danger is by and large a subjective yet data-based decision-making process. Human experts analyse heterogeneous data volumes, diverse in scale, and conclude on the avalanche scenario based on their experience. Nowada ...

2022