Jonathan Gagné
Scientific Advisor at Planétarium Rio Tinto Alcan
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolJonathan Gagné is an astrophysics researcher and Scientific Advisor at the Planétarium Rio Tinto Alcan in Montreal with 11 years of experience studying brown dwarfs, exoplanets, and young stellar associations. He combines observational expertise—over 200 nights across major telescopes and near-infrared spectroscopy—with large-scale data analysis, notably exploiting ESA Gaia’s transformative astrometry to map the Solar neighborhood. His career includes prestigious fellowships (NASA Sagan, Banting) and an academic role as Associate Professor at Université de Montréal, where he developed Bayesian methods to identify low-mass and planetary-mass objects. Jonathan advises public-facing planetarium exhibits, bridging research and science communication, and maintains an unexpected sideline as a coffee-brewing blogger at coffeeadastra.com. He is skilled at integrating precision radial-velocity and atmospheric retrieval techniques to characterize isolated and companion giant planets.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (PhD), Astrophysics, Doctor of Philosophy (PhD), Astrophysics at Université de Montréal
French, English, Spanish
Github Skills (23)
particle10
classifier10
python9
bayesian9
raw-sql9
astrology8
adam8
astronomy8
journal7
orbital-mechanics7
finder7
open-access6
astropy6
pandas-dataframe6
imaging6
Programming languages (2)
Github contributions (5)
jgagneastro/finder_charts
Dec 2017 - Jun 2023
This Python program pulls data from various astrophysics imaging surveys to create a multi-bands finder chart. Parts of this code are based on previous work by Adam Schneider and Michael Cushing. An online tool based on this code can be found at http://www.astro.umontreal.ca/~gagne/finderchart.php
Contributions:1 release, 12 pushes, 1 branch in 5 years 7 months
astrologypythonastrochartastrophysics
jgagneastro/mocapy
Aug 2022 - Jun 2026
mocapy is a Python package to interact with the Montreal Open Clusters and Associations (MOCA) database and can be used to obtain pandas DataFrames from raw SQL queries
Contributions:1 review, 5 PRs, 46 pushes in 3 years 10 months
databasepandas-dataframepythonraw-sql
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