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
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
Mentioned in
June 10, 2024
SDSC National Calls | Watch our webinar replays from June 10th
SDSC National Calls | Watch our webinar replays from June 10th
Learn more about our 1st National Calls for collaborative projects.
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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