Scholar
Kevin Scaman
Google Scholar ID: uiR63a8AAAAJ
Research scientist, INRIA
Citations & Impact
Citations
1,801
H-index
14
i10-index
17
Publications
20
Co-authors
7
list available
Publications
Resume (English only)
Academic Achievements
- 2018 Best paper award (4 out of 4865 submissions) at NeurIPS 2018, Montréal; 2020 Individual gold medal award, Huawei, Paris; 2019 Outstanding contributions individual award, Huawei, Paris; 2018 Future star award, Huawei, Paris.
Research Experience
- 2022 - present: Part-time associate professor, Ecole Polytechnique, Saclay; 2021 - present: Researcher, INRIA and ENS, Paris; 2018 - 2021: Principal researcher, Huawei Noah's Ark, Paris; 2017 - 2018: Post-doctoral researcher, Microsoft Research - INRIA joint center, Saclay.
Education
- 2013 - 2016: PhD in Applied Mathematics, Ecole Normale Supérieure Paris-Saclay, supervised by Nicolas Vayatis; 2011 - 2012: Msc in Machine Learning (MVA), Ecole Polytechnique; 2008 - 2011: Eng. deg in Applied Mathematics, Ecole Polytechnique.
Background
- Research interests include machine learning, optimization, and graph theory. Previously, a research scientist at Huawei's machine learning lab, leading the optimization for ML project-team. Conducted post-doctoral research in distributed optimization at the Microsoft Research – Inria Joint Center.
Miscellany
- Research focuses on the intersection of machine learning, structured data analysis (graphs, time series), and optimization. Specifically, analyzing the impact of structure in data (spatial proximity, time dependency, or item correlations) and using it for ML purposes such as training large-scale models and improving low-dimensional representations of graphs.
