Profile
Vincent Quenneville-Bélair, PhD, Applied Mathematician.
Design deep learning attention-based models to forecast product demand for supply chain optimization.
Develop foundation forecasting model, unifying across products worldwide at multiple scales, deploying zero-shot for external partners.
Create torchaudio library, engaging over 200 open source contributors.
Develop speech-to-text and text-to-speech deep learning models.
Integrate novel PyTorch optimizers collaborating with academic and industrial researchers.
Generate long-term strategic inventory capacity forecast. Model counterfactual scenarios. Optimize supply chain expansion recommendations.
Build causal impact models to estimate advertising campaign lift. Infer future returns and optimize advertising portfolio.
Teach internal machine learning specialization course series on matrix factorization, dimensionality reduction, and recommender systems.
Develop web-based software to automatically extract information from structured and unstructured data on the fly. Process the information to programmatically generate relevant visualizations and intelligent insights.
Model gravitational wave propagation to understand black hole collisions. Create and analyze novel specialized mixed finite element methods to simulate these models numerically.
Vincent Quenneville-Bélair, PhD, Applied Mathematician.