Welcome!

Ismael Mendoza


Hi, I'm Ismael! I'm a third-year Physics PhD student at the University of Michigan, advised by Camille Avestruz and Jeffrey Regier. I completed my BS in Physics (2018) and MS in Computer Science (2019) at Stanford University, where I was advised by Patricia Burchat.

My research focuses on developing novel machine learning techniques to solve problems in cosmology. I am also an active full member and sprint coordinator for the LSST Dark Energy Science Collaboration (DESC).

Here is my academic CV.

Papers

Scalable Bayesian Inference for Detection and Deblending in Astronomical Images
Derek Hansen and Ismael Mendoza (equal contribution), Runjing Liu, Ziteng Pang, Zhe Zhao, Camille Avestruz, Jeffrey Regier. Accepted to the ICML 2022 Workshop on Machine Learning for Astrophysics.
Link.




Bayesian Light Source Separator (BLISS): Probabilistic Detection, Deblending and Measurement
Ismael Mendoza, Runjing Liu, Derek Hansen, Zhe Zhao, Ziteng Pang, Camille Avestrz, Jeffrey Regier, and the LSST Dark Energy Collaboration.
in prep.




MultiCAM: Connecting Halo Properties with their Accretion Histories
Ismael Mendoza, Philip Mansfield, Kuan Wang, and Camille Avestruz.
in prep.




Effects of Overlapping Sources on Cosmic Shear Estimation: Statistical Sensitivity and Pixel-Noise Bias
Javier Sanchez, Ismael Mendoza, David P. Kirkby, Patricia Burchat, and the LSST Dark Energy Science Collaboration.
Link.

Presentations

Bayesian Light Source Separator (BLISS): Fully Probabilistic detection, deblending, and measurement
Ismael Mendoza
Dark Energy Science Collaboration (DESC) Summer 2022 Meeting
Chicago, IL. August 2022
Poster.

Scalable Bayesian Inference for Detection and Deblending in Astronomical Images
Ismael Mendoza
ICML 2022 Workshop on Machine Learning for Astrophysics
Baltimore, MA. July 2022
Poster.

Machine Learning in Cosmology
Ismael Mendoza
Physics Graduate Student Symposium 2022
Ann Arbor, MI. July 2022
Slides.

Bayesian Light Source Separator (BLISS) Update
Ismael Mendoza
Dark Energy Science Collaboration (DESC) Bayesian Pipelines Topical Team
April 2022 (virtual)
Slides.

Bayesian Light Source Separator (BLISS): Fully Probabilistic detection, deblending, and measurement
Ismael Mendoza
Dark Energy Science Collaboration (DESC) Winter 2022 Virtual Meeting
February 2022 (virtual)
Poster.

Bayesian Light Source Separator (BLISS) Update
Ismael Mendoza
Dark Energy Science Collaboration (DESC) Blending Working Group Meeting
February 2022 (virtual)
Slides.

Connecting the Properties of Dark Matter Haloes with Their Growth
Ismael Mendoza
University of Michigan Clusters Group
Ann Arbor, MI. March 2021 (virtual)
Slides.

Effects of overlapping sources on cosmic shear estimation: Statistical sensitivity and pixel-noise bias
Javier Sanchez & Ismael Mendoza
Collaboration-Wide Presentation for the Dark Energy Science Collaboration (DESC)
February 2021 (virtual)
Slides.

Bayesian Light Source Separator (BLISS)
Ismael Mendoza
Dark Energy Science Collaboration (DESC) Summer 2020 Virtual Meeting
Chicago, IL. July 2020 (virtual)
Poster.

Blending ToolKit Tutorial
Ismael Mendoza
Dark Energy Science Collaboration (DESC) Summer 2020 Virtual Meeting
Chicago, IL. July 2020 (virtual)
Slides.

The Blending Problem in Cosmology
Ismael Mendoza
Physics Graduate Student Symposium 2020
Ann Arbor, MI. July 2020 (virtual)
Slides.

BlendingToolKit: Walkthrough and Future Plans
Ismael Mendoza
DESC Blending Working Group Meeting
July 2020 (virtual)
Slides.