Samuel Vaiter is a senior research scientist based in Nice with 14 years of experience at CNRS focused on machine learning and mathematical optimization. He specializes in bilevel optimization and algorithmic development, translating advanced theory into practical methods for imaging and learning problems. His career traces a steady academic progression from PhD and postdoc work in optimization and computer vision to senior research leadership at France's leading national research center. Samuel combines deep mathematical training from École normale supérieure Paris-Saclay with hands-on experience in image processing and graph-visualization projects applied to neurology. Colleagues value his ability to bridge rigorous analysis and implementable algorithms, often addressing nested optimization challenges that others avoid. He is known for pursuing technically challenging problems that yield both theoretical insight and usable computational tools.
13 years of coding experience
10 years of employment as a software developer
Master 2, Mathematics, Computer Vision and Machine Learning, Master 2, Mathematics, Computer Vision and Machine Learning at École normale supérieure Paris-Saclay
Contributions:1 push, 1 branch, 1 issue in 2 years 3 months
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