Guillaume Obozinski

Guillaume Obozinski

Deputy Executive Director & Chief Data Scientist
Academia
Leadership & Administration
(Alumni)

Guillaume Obozinski graduated with a PhD in Statistics from UC Berkeley in 2009. He did his postdoc and held until 2012 a researcher position in the Willow and Sierra teams at INRIA and Ecole Normale Supérieure in Paris. He was then Research Faculty at Ecole des Ponts ParisTech until 2018. Guillaume has broad interests in statistics and machine learning and worked over time on sparse modeling, optimization for large scale learning, graphical models, relational learning and semantic embeddings, with applications in various domains from computational biology to computer vision.

Projects

ML-L3DNDT

Completed
Robust and scalable Machine Learning algorithms for Laue 3-Dimensional Neutron Diffraction Tomography
Big Science Data

STIMO

In Progress
Personalized epidural electrical stimulation of the lumbar spinal cord for clinically applicable therapy to restore mobility after paralyzing spinal cord injury

VOCIM

In Progress
Directed Imitation During Vocal Learning

ML-Spock

In Progress
Machine Learning Supported System for Performance Assessment of Steel Structures Under Extreme Operating Conditions and Management of Risk

CHEMSPEC

In Progress
Cost-effective chemical speciation monitoring of particulate matter air pollution

PAIRED-HYDRO

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

FastPlasmaSim

In Progress
Acceleration of Free-boundary Grad-Shafranov codes using advanced numerical methods
Energy, Climate & Environment

SPEED2ZERO

In Progress
Sustainable pathways towards net zero Switzerland
Energy, Climate & Environment

DrSCS

In Progress
Predicting subclonal drug response from single-cell sequencing for precision oncology
Biomedical Data Science

MLfusion

In Progress
Machine Learning for Disruption Prediction in Tokamaks
Energy, Climate & Environment

WATRES

In Progress
A Data-Driven approach to estimate WATershed RESponses
Energy, Climate & Environment

EXPECTmine

In Progress
Mining Toxicity and High Resolution Mass Spectrometry Data for Linking Exposures to Effects
Energy, Climate & Environment

ML4FCC

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

4D-Brains

Completed
Extracting Activity from Large 4D Whole-Brain Image Datasets
Biomedical Data Science

AURORA

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

MLTox

In Progress
Enhancing toxicological testing through machine learning
Energy, Climate & Environment

PolyNet

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

NLP

Narratives in Law and Politics: A Computational Linguistics Approach
Digital Administration

4Real

Real-time urban pluvial flood forecasting
Energy, Climate & Environment

MLATEM

Machine Learning tools for Analytical Transmission Electron Microscopy
Big Science Data

COVID-19

Completed
Epidemic Forecasting
Biomedical Data Science
Big Science Data
Digital Administration

EXPECT

EXtending the PrEdiCTability of the Atmosphere over Europe
Energy, Climate & Environment

SenseDynamics

Completed
Predicting aerodynamics forces from sensor data

DEAPSnow

Completed
Improving snow avalanche forecasting by data-driven automated predictions
Energy, Climate & Environment

PACMAN LHC

Completed
Particle Accelerators and Machine Learning
Big Science Data

MSEI

Completed
Molecular structure elucidation by integrating different data mining strategies
Energy, Climate & Environment

EconMultiplex

Completed
Multiplex Networks in International Trade
Digital Administration

Neuro-choice

Completed
Extracting Neural Activity Signals from Large-scale Calcium Imaging Data
Biomedical Data Science
Big Science Data

DASH

Completed
DAta Science-informed attribution of changes in the Hydrological cycle
Energy, Climate & Environment

Publications

Donner, C.; Bartram, J.; Hornauer, P.; Kim, T.; Roqueiro, D.; Hierlemann, A.; Obozinski, G.; Schröter, M."Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains"204.0e1011964
Jones, C.; Barzegar-Keshteli, M.; Gross, A.; Obozinski, G.; Rahi, S. J."A Graph Matching Approach to Tracking Neurons in Freely-Moving C. elegans"
Jones, C.; Barzegar-Keshteli, M.; Gross, A.; Obozinski, G.; Rahi, S. J."A Graph Matching Approach to Tracking Neurons in Freely-Moving C. elegans"
Teurtrie, A.; Perraudin, N.; Holvoet, T.; Chen, H.; Alexander, D. T.; Obozinski, G.; Hébert, C."espm: A Python library for the simulation of STEM-EDXS datasets"249113719
Harris, E.; Gasser, L.; Volpi, M.; Perez-Cruz, F.; Bjelić, S.; Obozinski, G."Harnessing data science to improve molecular structure elucidation from tandem mass spectrometry"345.01935-1950
Donner, C.; Tagasovska, N.; He, G.; Mulleners, K.; Shimazaki, H.; Obozinski, G."Learning interpretable latent dynamics for a 2D airfoil system"
Pérez-Guillén, C.; Hendrick, M.; Techel, F.; van Herwijnen, A.; Volpi, M.; Olevski, T.; Pérez-Cruz, F.; Obozinski, G.; Schweizer, J."Data-driven automatic predictions of avalanche danger in Switzerland"EGU General Assembly Conference AbstractsEGU21–61542021
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 ConferenceIPAC20212021
Krymova, E.; Obozinski, G.; Schenk, M.; Coyle, L. T.; Pieloni, T."Data-driven modeling of beam loss in the LHC"2022

Mentioned in

November 4, 2024

MeteoSwiss and the SDSC join forces

MeteoSwiss and the SDSC join forces

The Federal Office of Meteorology and Climatology (MeteoSwiss) and the Swiss Data Science Center have signed a framework agreement.
October 25, 2023

Computerworld | AI predicts avalanche danger [In German]

Computerworld | AI predicts avalanche danger [In German]

The AI project "DEAPSnow" takes avalanche forecasting to a whole new level.
October 9, 2023

DEAPSnow | AI for avalanche forecasting

DEAPSnow | AI for avalanche forecasting

“DEAPSnow”, a project by the Swiss Data Science Center (SDSC) and the WSL Institute for Snow and Avalanche Research SLF, developed an Artificial Intelligence (AI) to support avalanche forecasters in creating the avalanche bulletin. This product provides essential information about the prevailing snow and avalanche conditions in the Swiss Alps and the Jura.
February 21, 2023

Major Swiss research institutes join forces for strong data science

Major Swiss research institutes join forces for strong data science

A framework agreement was signed by the Swiss Federal Institutes of Technology, the CHUV, and UNIL to establish a common base of expertise in the area of data science and serve projects in the healthcare sector.

Case Studies

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