People
The ART is made up of researchers across astrophysics, statistics, and data science spanning a wide range of career stages. More information about individual members of the group can be found below.
Faculty
Postdoctoral Researchers

Ronan KerrPersonal Website
Ronan is a Dunlap Postdoctoral Fellow who works on novel observational techniques that broaden our knowledge of star formation within our galaxy. He aims to reconstruct recent star formation history using Gaia and Sloan Digital Sky Survey V (SDSS-V) data of young stars with a goal of creating the time-resolved star formation map in the last 50 Myrs. He received his Ph.D. at the University of Texas at Austin under the supervision of Adam Kraus. Outside of research, Ronan is interested in astronomy and science outreach programs. He also enjoys stargazing, amateur astronomy, and astrophotography.
Graduate Students

Anika SlizewskiAnika is a 5th-year Ph.D. student at the David A. Dunlap Department of Astronomy & Astrophysics who works with Gwen Eadie, Ting Li, and Jo Bovy on improving statistical methods of estimating masses of astronomical systems. They are interested in uncertainty analysis and have done work with outlier detection and dimensionality reduction of multiwavelength image data. Anika's long-term goal is to develop a consistent and accurate way to combine data from multiple types of populations to estimate properties of the Galaxy.

Phil Van-LanePhil is a 5th-year Ph.D. candidate in the David A. Dunlap Department of Astronomy & Astrophysics co-supervised by Gwen Eadie and Josh Speagle as well as Ryan Cloutier (McMaster). His research focuses on leveraging machine learning and statistical methods to develop stellar dating methods using rotation and magnetic activity data, with a focus on low-mass stars known as M-dwarfs. His long-term goal is to build a catalogue of M-dwarf ages and use these constraints to inform stellar activity and exoplanet evolutionary analyses.
Undergraduate Students
ART Associates

Andrew SaydjariPersonal Website
Andrew is an Assistant Professor in the Department of Astronomy at New Mexico State University. His research focuses on combining astrophysics, statistics, and high-performance coding to study the chemical, spatial, and kinematic variations in the dust that permeates the Milky Way. He believes knowledge comes from data, and data comes from instruments - a view that shapes his approach to science. He is also passionate about scientific communication, open source software/data availability, and the replication crisis. He was previously a NASA Hubble Postdoctoral Fellow at Princeton University and received his Ph.D. in Physics from Harvard University in 2024.
Collaborators

Laurence Perreault-LevasseurPersonal Website
Laurence is an Assistant Professor at the Université de Montréal and Canada Research Chair in Computational Cosmology and Artificial Intelligence, a member of the Ciela Institute and an associate academic member of Mila. Her research develops and applies machine learning methods to cosmology.
Recent Alumni

David (Dayi) Li (PDF '25-26)Personal Website
David is now an NSERC Canada Postdoctoral Research Award Fellow at the University of Waterloo. He completed his Ph.D. at the University of Toronto working with Gwen Eadie, Patrick Brown, and Roberto Abraham, developing spatial point process models to detect and study elusive Ultra-Diffuse Galaxies alongside fast, approximate Bayesian computational methods for large and complex statistical models.