Loic Landrieu
Chercheur at MEEDDM
Paris, Ile-de-France
Summary
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Rockstar🎓
Top SchoolLoic Landrieu is a researcher at École des Ponts ParisTech and a seasoned specialist in machine learning, computer vision, and geospatial data with nine years of experience bridging academic research and applied engineering. His PhD work and ongoing research focus on structured models on weighted graphs and large-scale point cloud semantic segmentation, exemplified by his well-maintained open-source Superpoint Graph project. Based in Paris, he has held research and teaching roles at INRIA, the French Mapping Agency, and ENPC, and has taught introductory machine learning and graphical models. Loic combines strong mathematical training from École Normale Supérieure and École Polytechnique with practical impact in geospatial ML, often translating theoretical models into production-ready code. He is equally comfortable publishing in academic venues and maintaining production repositories, reflecting a rare blend of rigorous theory and reproducible engineering. An understated strength is his continuity across public-sector engineering (MEEDDM) and frontier research, enabling solutions that are both scientifically robust and operationally relevant.
9 years of coding experience
2012, Applied Mathematics, 2012, Applied Mathematics at Ecole normale supérieure2012, Computer Science, Applied Mathematics, 2012, Computer Science, Applied Mathematics at Ecole polytechniqueMS PAPDD, Public Policy Analysis, MS PAPDD, Public Policy Analysis at AgroParisTech - Institut des sciences et industries du vivant et de l'environnement2012, Computer and Information Sciences, Valedictorian, 2012, Computer and Information Sciences, Valedictorian at Ecole nationale des Ponts et Chaussées
English, German
Github Skills (11)
semantic-segmentation10
pytorch10
machine-learning10
image-segmentation10
segmentation10
graph-neural-network10
point-cloud10
python10
clustering10
large-scale9
lidar9
Programming languages (5)
Github contributions (5)
loicland/superpoint_graph
Nov 2017 - May 2022
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:88 commits, 9 PRs, 207 pushes in 4 years 6 months
Contributions summary:The user, Loic Landrieu, appears to be a primary contributor to the project. Their commits primarily involve core development tasks such as adding and modifying code, updating documentation, and managing the project's structure, including the creation and deletion of license files. A significant portion of the commits involved code related to point cloud processing, semantic segmentation, and graph structures, implying expertise in these areas. The user also appears to be actively releasing and maintaining the project.
semantic-segmentationpoint-cloudautoencoderlarge-scalegraphs
loicland/point-cloud-regularization
May 2017 - Mar 2020
A structured optimization framework for spatially regularizing point clouds classification
Contributions:51 commits, 4 PRs, 50 pushes in 2 years 10 months
point-cloudsoptimization-frameworkstructuredoptimizationpoint
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