cv
CV of Tristan
Basics
Name | Tristan Lazard |
Label | PhD in Computational Pathology |
trislaz.tl@gmail.com | |
Phone | +336.89.95.84.82 |
Url | https://trislaz.github.io/ |
Summary | After completing my undergraduate studies in biology at ENS Ulm, I pursued and graduated with a Master's degree in Applied Mathematics from UPMC Sorbonne. Then, I earned my PhD from CBIO at Mines ParisTech. My doctoral research bridged the fields of biology, mathematics, and computer science, with a particular focus on developing algorithms to learn representations of large-scale microscopy images (WSIs). My interests broadly span these areas, including biology and evolution, applied mathematics, as well as computer science and machine learning. |
Education
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2018 - 2019 Paris, 75006
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2016 - 2017 Paris
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2013 - 2016 Paris
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2011 - 2013 Paris
Work
- 2019.12 - 2023.11
PhD Candidate
CBIO - Mines-Paristech
During my PhD, I focused on training predictive models from Whole Slide Images of cancerous tissues. Besides their clinical use, my goal was to understand these models to improve our understanding of the disease. I also worked on developing unsupervised techniques to train representations of these biological samples. This effort resulted in 5 papers, 1 patent, and a prize-winning solution at an international data challenge, Visiomel.
- 2019.01 - 2019.07
Engineering Intern
CMM, Mines-Paristech
In partnership with L’Or´eal, I created an algorithm for automatically counting melanocytes in microscopic images. This solution has been integrated into the processing pipeline and is now utilized in regular research.
- 2018.01 - 2018.08
Research Intern
IBPS, Sorbonne University, AIRE team
I developped an algorithm for calculating phylogenetic trees from huge genetic sequence data (-omics data).
- 2017.03 - 2017.07
Research Intern
Collège de France, SMILE team
I worked on a model of random mutualistic network. I studied its asymptotic behaviours and developed an algorithm to infer its parameters from a sampled network.