Mathieu Pont
Post-doctoral Researcher at Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU)
Germany
Summary
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Senior🎓
Top SchoolMathieu Pont is a post-doctoral researcher with eight years of experience bridging Topological Data Analysis, machine learning and visualization, now based at RPTU Kaiserslautern-Landau after completing a PhD at CNRS Sorbonne Université (LIP6). His doctoral work produced practical tools for comparing and summarizing ensembles of scalar fields—defining a new metric for merge trees and adapting PCA and autoencoder frameworks to Wasserstein spaces of merge trees and persistence diagrams. He combines strong theoretical foundations with applied research, delivering algorithms for geodesics, barycenters, and clustering tailored to topological summaries. Comfortable across Python research stacks and visualization pipelines, he also has early experience applying NLP and reinforcement learning in biomedical and agent-based benchmarks. Colleagues value him for turning abstract topological concepts into computable methods with clear machine-learning and visualization impact.
8 years of coding experience
1 year of employment as a software developer
Licence, Informatique, Licence, Informatique at Université Paul Sabatier Toulouse IIIMaster, Artifical Intelligence - Machine Learning for Data Science, Master, Artifical Intelligence - Machine Learning for Data Science at Université Paris Cité
English, French
Github Skills (20)
visualization10
python10
paraview10
topology10
ttk10
topological-data-analysis10
data-visualization10
vtk10
data-analysis10
clip5
pytorch4
deep-learning4
bert4
nlp4
openai3
Programming languages (3)
Github contributions (5)
MatPont/WassersteinMergeTreesData
Jun 2021 - May 2022
Contributions:6 commits, 5 pushes, 1 branch in 10 months
MatPont/Text_Mining_Project
Jan 2020 - Mar 2020
Contributions:43 commits, 4 pushes in 1 month
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