Morgan Fouesneau

I'm

Morgan Fouesneau

Engineer | Astrophysicist | Data Scientist

Max Planck Institute for Astronomy

About Me

I am an astronomer and an engineer with 10+years of experience in terabyte data manipulation technologies, cloud computing, pipeline design, machine learning, as well as more than 5 years as a project manager in astronomy. I am part of the Astronomy Data Science Department at the Max Planck Institute for Astronomy. I regularly contribute to many data modeling and probabilistic inference in computer science projects, organic components studies, particle detector calibration, and space weather applications. My personal research focuses primarily on where stars form in galaxies linking them to the cosmological context through their chemical patterns and dynamical properties.

Interested in astronomy and data analysis puzzles

Technical expertise

  • Python, C++, Java, Javascript, CSS
  • MySQL, PostgreSQL, ADQL
  • VSCode, IntelliJ Idea, Eclipse, Maven, SVN, git
  • HPC, Cloud Computing, AWS, XSEDE

Interests

  • Statistics, Machine learning, and data mining
  • Terabyte dataset manipulation and scaling up solutions
  • Collaborative software development
  • Star formation and evolution
  • Interstellar medium & dust
  • Career Training & Development

Recent Posts

View all posts

Gaia Data Release 3

achivement of five years of intense work through adversity.

Last updated on 2022-06-13 · 4min read · Gaia

Updating my website, blogging perspective

New year, new role, new resolutions. I am planning to write a bit more and I need a good setup.

Last updated on 2022-05-17 · 2min read · Setup, Website

Estimating an article's reading time in python

Offering reading time estimation can contribute greatly to the end users' experience. I use it on my website and here is how I implemented it.

Last updated on 2022-05-17 · 2min read · python, code, Website

Empirical flux calibration of Coronagraph observations

A problem that requires flux calibration of low spectral resolution time series data.

Last updated on 2022-04-11 · 1min read · data-driven, modeling

MPIA Arxiv Display

I spent a significant amount of time to update the way we show ArXiv papers at the institute. I decided to completely outsource the process to GitHub using the GitHub Actions.

Last updated on 2022-04-07 · 1min read · data-driven, astrophysical parameters

Featured Projects & Research

A small selection of current projects and research.

  • All
  • Code
  • Gaia

Data-driven Stellar Models

Going beyond the synthetic stellar atmospheres combined with isochrones and extinction curves.

Gaia Unlimited

Who is In, and Who is Not? Determining the Gaia Survey Selection Function

Gaia Astrophysical Parameters

As part of the Gaia collaboration (DPAC), we are developing methods to estimate the astrophysical parameters of Gaia sources.

Resume

Experience

2021 - Present

Astrophysicist | Senior Data Scientist

Max Planck Institute for Astronomy, Germany

  • Building the data science department at MPIA
  • Supports MPIA scientists to carry out novel, cutting-edge research
  • Solidify foundational hacking & coding skills
  • Provide a space to explore and develop data science skills
  • Networking, outside presence and broader impact
  • Tenure position

C++, Python, Java, IntelliJ Idea, Eclipse, HPC, Machine Learning, project management, databases

2014 - 2021

Postdoc | Gaia & 4MOST unit manager

Max Planck Institute for Astronomy, Germany

  • Leading validation of astrophysical parameter in the Gaia consortium (Coordination Unit 8).
  • Consulting on the Gaia classification and spectral analysis development – DSC & GSP-Phot sofware.
  • Leading the spectral classification unit and pipeline for the 4MOST observations.
  • Initiating and developing the 4MOST classificaiton pipeline - 4CP.

Python, Java, C++, IntelliJ Idea, Eclipse, HPC, Machine Learning, project management, databases

2011 - 2014

Postdoc | Semi-resolved populations in galaxies

University of Washington, WA, USA

  • Coordinating development of new inference methods for star and cluster formation histories.
  • Consulting on probabilistic analysis of stellar populations, initial mass function & extinction.
  • Leading the spectral classification unit and pipeline for the 4MOST observations.
  • Leading computing resources transitions to national cluster (XSEDE) and Amazon Cloud.
  • Co-leading the developement of the Bayesian Extinction and Stellar Tool - BEAST.
  • Leading the development of the photometric tool PyPhot.
  • Consulting on "the Andromeda Project" Zooniverse platform - andromeda-project.

Python, C++, Database, SQL, HPC, Cloud Computing, Citizen Science, Probabilistic Modeling

Education

2010

PhD in Astrophysics

University of Strasbourg, France

"Study of stellar cluster populations in galaxies, a Bayesian approach" manuscript

Python, Probabilistic Modeling, Forward modeling

2007

Master degree in Astrophysics

University of Strasbourg, France

Master project with Matthew Ashby and Joseph Hora at CfA - Harvard Smithonian on temporal analysis in the Spitzer's "IRAC calibration field" (IRACCF)".

Databases, Time series, Python, Probabilistic Modeling, Forward modeling, compact objects, high energy, galactic evolution

2007

Engineer degree in Fundamental physics, simulations & signal processing

Télécom Physique Strasbourg, France

Fundamental physics, Signal processing, Parallel computing, ddatabases, Engineering, Simulations

Participations in Inter-Disciplinary Collaborations

2013 - 2015

Consulting Scientist | Calibration of the gamma ray detector AGATA

GSI, Germany

Ph.D project of Damian Ralet at the Helmholtz Centre for Heavy Ion Research

Python, Probabilistic Modeling, Machine Learning, Instrument Calibration, Nuclear Physics, High Energy

2013 - 2014

Consulting Scientist | Machine learning to detect artifacts in astronomical images

Computer Science dept., University of Washington, WA, USA

Master project of Martina Unutzer & prof. Magdalena Balazinska

Computer Science, Image segmentation, Machine learning, Distributed databases, Dashboard

2010 - 2014

Consulting Scientist | Organic solar cells & Carbon Nanotube Networks

Ingineer, Informatics & Imaging laboratory (ICube), France

Collaboration with Dr. Yann Leroy

  • Stochastic model of physical parameters of organic solar cells - Raba et al. 2017
  • Probabilistic percolation modeling in Carbon Nanotube Networks - Heitz et al. 2011

Python, Java, Comsol, Stochastic model, Monte-Carlo methods, probabilistic inference

2006 - 2009

Consulting Engineer Scientist | Solar Weather Research

LESIA & International Space University, France

Collaboration with Dr. Isabelle Scholl from ISU & Dr. Jean Aboudarham at LESIA

Solar weather, feature tracking, Neural Networks, Probabilistic Inference, temporal analysis, IDL

Recent Publications

ADS Search
Arxiv Search


h-index: 53
87 refereed publications
46 publications from large collaborations
23 other publications
6,575 citations
(from non-collaboration papers)

View all publications

Showing 5 most recent non-collaboration articles from ADS

2024
  • "Uniting Gaia and APOGEE to unveil the cosmic chemistry of the Milky Way disc"
    Cantat-Gaudin, T., Fouesneau, M., Rix, H.-W., Brown, A. G. A., Drimmel, R., Castro-Ginard, A., Khanna, S., Belokurov, V., Casey, A. R., 2024, arXiv e-prints, - [0 citations]
    2024arXiv240105023C
  • "Dissecting the Gaia HR diagram - II. The vertical structure of the star formation history across the solar cylinder"
    Mazzi, A., Girardi, L., Trabucchi, M., Dalcanton, J. J., Luger, R., Marigo, P., Miglio, A., Costa, G., Chen, Y., Pastorelli, G., Fouesneau, M., Zaggia, S., Bressan, A., Dal Tio, P., 2024, Monthly Notices of the Royal Astronomical Society, 583 [1 citations]
    2024MNRAS.527..583M
  • "Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers"
    Huppenkothen, D., Ntampaka, M., Ho, M., Fouesneau, M., Nord, B., Peek, J. E. G., Walmsley, M., Wu, J. F., Avestruz, C., Buck, T., Brescia, M., Finkbeiner, D. P., Goulding, A. D., Kacprzak, T., Melchior, P., Pasquato, M., Ramachandra, N., Ting, Y.-S., van de Ven, G., Villar, S., Villar, V. A., Zinger, E., 2023, arXiv e-prints, - [2 citations]
    2023arXiv231012528H
2023
  • "Estimating the selection function of Gaia DR3 subsamples"
    Castro-Ginard, A., Brown, A. G. A., Kostrzewa-Rutkowska, Z., Cantat-Gaudin, T., Drimmel, R., Oh, S., Belokurov, V., Casey, A. R., Fouesneau, M., Khanna, S., Price-Whelan, A. M., Rix, H.-W., 2023, Astronomy and Astrophysics, A37 [11 citations]
    2023A&A...677A..37C
  • "The Panchromatic Hubble Andromeda Treasury. XX. The Disk of M31 is Thick"
    Dalcanton, J. J., Bell, E. F., Choi, Y., Dolphin, A. E., Fouesneau, M., Girardi, L., Hogg, D. W., Seth, A. C., Williams, B. F., 2023, The Astronomical Journal, 80 [3 citations]
    2023AJ....166...80D

Contact

Max-Planck-Institut für Astronomie

Königstuhl 17, Heidelberg, BW 69117

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