Paul Raynaud
Machine Learning Engineer at Vega BioImaging Technologies Inc.
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolPaul Raynaud is a machine learning engineer with a PhD in mathematics and eight years of experience applying advanced modeling and optimization to real-world problems. Based in Montreal, he builds and deploys computer-vision pipelines for pathological tissue analysis, from dataset orchestration and hyperparameter tuning on AWS GPUs to cloud service deployment and quantitative biomarker metrics. His background in operational research and formal verification informs a rigorous approach to model reliability, segmentation and per-cell classification, and nanoparticle detection for immunohistochemistry. He also teaches optimization and algorithm design at the university level, bridging theory and practice across graduate and undergraduate audiences. Notably, his work blends deep mathematical training with hands-on ML engineering to translate academic techniques into regulated biomedical software.
8 years of coding experience
Master 1 (M1) Computer science, Master 1 (M1) Computer science at Université Grenoble Alpesdoctoral degree Maths, doctoral degree Maths at Polytechnique MontréalMaster 2 (M2) Operational Research and Combinatorial Optimization, Master 2 (M2) Operational Research and Combinatorial Optimization at Université Grenoble Alpes; Grenoble INP
Github Skills (41)
linear-systems10
linear-operators10
splines10
linear-algebra9
nonlinear-optimization9
optimization9
julia9
region9
entropy9
factorization8
hsl8
optimizer8
inheritance8
optimization-methods8
trust7
Programming languages (4)
Github contributions (5)
JuliaSmoothOptimizers/ExpressionTreeForge.jl
May 2020 - Dec 2022
Contributions:14 reviews, 35 commits, 59 PRs in 2 years 7 months
JuliaSmoothOptimizers/KnetNLPModels.jl
Jan 2022 - Sep 2022
An NLPModels Interface to Knet
Contributions:82 reviews, 20 commits, 56 PRs in 8 months
deep-learningknetnlpmodelsoptimizationneural-networks
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