People
On this page
Current members are listed first: faculty, postdoctoral researchers, graduate students, and undergraduate students. ART associates, collaborators, and recent alumni follow, and each entry links to that person's own site where they have one.
Faculty
Gwendolyn Eadie
On leave until November 2026.
Gwen is an Associate Professor of Astrostatistics, jointly appointed between the David A. Dunlap Department of Astronomy & Astrophysics (51%) and the Department of Statistical Sciences (49%). She is also a member of the Data Sciences Institute. Her research interests include hierarchical Bayesian inference, generalized linear models, spatial point processes, and time series analysis for the study of the Milky Way Galaxy, ultra-diffuse galaxies, star clusters and globular clusters, stars and stellar flares, and fast radio bursts.
Joshua S. Speagle (沈佳士)
Josh is an Assistant Professor of Astrostatistics, jointly appointed between the Department of Statistical Sciences (51%) and the David A. Dunlap Department of Astronomy & Astrophysics (49%). He is also an associate of the Dunlap Institute for Astronomy & Astrophysics and a member of the Data Sciences Institute. His work focuses on using a combination of astronomy, statistics, data science, and artificial intelligence (AI) to analyze massive datasets containing billions of stars and galaxies to understand how galaxies like our own Milky Way (and the stars within it) form, behave, and evolve over time.
Postdoctoral Researchers
Jacqueline Antwi-Danso
Jacqueline is a Dunlap Postdoctoral Fellow at the David A. Dunlap Department of Astronomy & Astrophysics with a joint affiliation at the University of Massachusetts, Amherst. She completed her Ph.D. at Texas A&M University, where she worked with Casey Papovich on searching for the most massive galaxies in the distant Universe. Jacqueline was born and raised in the beautiful West African country of Ghana and has been involved with organizing outreach events and programs such as LUMA.
Jacqueline also works closely with Adam Muzzin at York University.
Tanveer Karim
Tanveer is a Dunlap Postdoctoral Fellow at the David A. Dunlap Department of Astronomy & Astrophysics and a member of the DESI and DESC collaborations. His current research interests include developing frameworks to constrain cosmological models by cross-correlating multiple surveys and improving our ability to interpret these constraints in order to address various cosmological tensions. Outside of research, Tanveer loves to learn languages, play board games, and read books.
Tanveer also works closely with Renée Hložek at the Dunlap Institute.
Kevin McKinnon
Kevin is an Eric and Wendy Schmidt AI in Science Fellow at the David A. Dunlap Department of Astronomy & Astrophysics whose research focuses on understanding how the Milky Way formed and evolved through Galactic Archeology. He combines hierarchical Bayesian models with Hubble Space Telescope and Gaia data to improve astrometry for faint stars, and works with SDSS-V to enhance APOGEE spectral pipelines.
Kevin also works closely with Aviad Levis in the Department of Computer Science.
Biprateep Dey
Biprateep is a Canadian Institute for Theoretical Astrophysics (CITA) and Dunlap Postdoctoral Fellow, having previously held an Eric and Wendy Schmidt AI in Science Fellowship. His work involves developing novel statistical machine learning tools to study the formation and evolution of galaxies and the Universe as a whole. He is interested in large astronomical surveys and has been deeply involved with the DESI collaboration. He is also passionate about developing a scientific community which is accessible and welcoming to all.
Duo Xu
Duo is a Canadian Institute for Theoretical Astrophysics (CITA) Postdoctoral Fellow, having previously held an Eric and Wendy Schmidt AI in Science Fellowship. His research interests focus on trying to use artificial intelligence (AI) to understand star formation, stellar feedback, and turbulence. Before joining the University of Toronto, Duo was a Virginia Initiatives on Cosmic Origins (VICO) Origin Postdoctoral Fellow at the University of Virginia. He received his Ph.D. from the University of Texas at Austin under the supervision of Stella Offner.
Duo also works closely with Peter Martin at the Canadian Institute for Theoretical Astrophysics (CITA).
Ronan Kerr
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.
Christian Kragh Jespersen
Christian is a joint Eric and Wendy Schmidt AI in Science and CITA National Fellow, spending his first two years at the University of Toronto co-supervised by Josh Speagle and Aviad Levis, followed by two years in Montréal with Laurence Perreault-Levasseur. His research integrates inductive biases and geometric and physical constraints into well-calibrated Bayesian and machine learning models, with a focus on galaxy formation and cosmology. He received his Ph.D. from Princeton University under the supervision of Peter Melchior and David Spergel.
Maryum Sayeed
Maryum is an Arts & Science Postdoctoral Fellow co-supervised by Gwen Eadie and Josh Speagle. Her research uses large photometric and spectroscopic surveys, and asteroseismology in particular, to probe the formation and evolution of the Milky Way and the stars within it. She is the lead developer of The Swan, a data-driven method for predicting stellar surface gravities. She received her Ph.D. from Columbia University and her B.Sc. from the University of British Columbia.
Chloe Cheng
Chloe is a Research Excellence Postdoctoral Fellow co-supervised by Seiji Fujimoto and Josh Speagle. Her research uses ultra-deep spectroscopy to measure elemental abundances and stellar population parameters, unravelling the formation and assembly histories of massive quiescent galaxies. She received her Ph.D. from Leiden Observatory under the supervision of Mariska Kriek, and her M.Sc. from the University of Waterloo.
Graduate Students
Anika Slizewski
Anika 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.
Alex Laroche
Alex is a 5th-year Ph.D. candidate in the David A. Dunlap Department of Astronomy & Astrophysics and Data Sciences Institute Doctoral Fellow co-supervised by Josh Speagle and Maria Drout. His research combines machine learning and stellar evolution to discover rare stellar populations in large-scale surveys and understand their nature through follow-up observations. He focuses on binary-stripped helium stars and carbon-enhanced metal-poor stars, and has developed data-driven models for Gaia spectra.
Phil Van-Lane
Phil 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.
Rodrigo Barradas Herrera
Rodrigo is a 4th-year Ph.D. student in the Department of Statistical Sciences co-supervised by Vianey Leos Barajas and Gwen Eadie. His research interests involve Hidden Markov Models (HMMs), including how they can be used to better understand stellar flares and magnetic activity.
Leo Watson
Leo is a 3rd-year Ph.D. student in the Department of Statistical Sciences and an Affiliate Researcher at the Vector Institute, co-advised by Radu Craiu and Josh Speagle. His research centres on uncertainty quantification, particularly distribution-free methods such as conformal prediction, alongside statistical learning and MCMC methods for Bayesian inference problems with astronomical data. He completed his B.S. in Statistics at the University of Toronto in 2024.
Ian Zhang
Ian is a 1st-year Ph.D. student in the Department of Statistical Sciences co-supervised by Josh Speagle and Thibault Randrianarisoa. His research develops approximate Bayesian methods for stellar and galactic inference directly from image-based data rather than converted tabular summaries, with the aim of reducing model misspecification in prior-sensitive models. He completed his Honours B.Sc. in Statistics and Mathematics and his M.Sc. in Statistics at the University of Toronto.
Isabelle (Liyuan) Huang
Isabelle is a 1st-year Ph.D. student in the Department of Statistical Sciences and a CANSSI Ontario Multidisciplinary Doctoral (Mdoc) trainee, supervised by Josh Speagle alongside Aviad Levis and Seiji Fujimoto. Her research addresses the statistical challenges of gravitationally-lensed galaxy surveys.
Undergraduate Students
Leo (Hanbang) Wu
Leo is an undergraduate researcher in the Summer Undergraduate Research Program (SURP) at the David A. Dunlap Department of Astronomy & Astrophysics, co-supervised by Josh Speagle alongside Biprateep Dey and Nolan Koblischke. He works on alphaUniverse, an AI virtual observatory that uses foundation-model embeddings to make survey data across images, spectra and time series searchable and comparable.
ART Associates
Aviad Levis
Aviad is an Assistant Professor in the Department of Computer Science with a cross-appointment to the David A. Dunlap Department of Astronomy & Astrophysics and an associate of the Dunlap Institute for Astronomy & Astrophysics. His research focuses on computational imaging and machine learning in astronomy and the natural sciences. He was previously a postdoctoral scholar at Caltech, where he worked on imaging the supermassive black hole at the center of the Milky Way as part of the Event Horizon Telescope collaboration. He received his Ph.D. from the Technion-Israel Institute of Technology in 2020.
Catherine Zucker
Catherine is an astrophysicist at the Center for Astrophysics | Harvard & Smithsonian. Her research focuses on developing novel techniques to map the 3D structure and dynamics of the Milky Way, combining observations, simulations, astrostatistics, and data visualization to study the interstellar medium and its connection to star formation. She is an expert in 3D dust mapping and has done pioneering work on the Local Bubble and large-scale galactic structures. She previously held a NASA Hubble Fellowship at the Space Telescope Science Institute and received her Ph.D. from Harvard University in 2020.
Haowen Zhang
Haowen is a Postdoctoral Fellow at the Canadian Institute for Theoretical Astrophysics (CITA). His research focuses on understanding empirical connections between dark matter halos, galaxies, and supermassive black holes across cosmic time. He developed TRINITY, a framework for inferring black hole masses and growth rates, and collaborates on preparations for next-generation missions including Euclid, Roman, and LSST. He received his Ph.D. from the University of Arizona in 2024.
Haowen also works closely with Josh Speagle at the David A. Dunlap Department of Astronomy & Astrophysics.
Connor Stone
Connor is a Rubin Postdoctoral Fellow at the David A. Dunlap Department of Astronomy & Astrophysics. His research focuses on cosmology using supernovae, approaching the problem in a fully Bayesian framework to address selection functions and the challenges of covariant photometric redshift, classification, and distance measurements. He also develops research software including AstroPhot, a fast and powerful astronomical image photometry solver. He received his Ph.D. from Queen's University in 2022.
Connor also works closely with Renée Hložek at the Dunlap Institute.
Andrew Saydjari
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.
Pinchen Fan
Pinchen is a Ph.D. candidate in the Department of Astronomy and Astrophysics at Penn State University and a visiting graduate student at the David A. Dunlap Department of Astronomy & Astrophysics. Her research centres on the search for extraterrestrial intelligence (SETI): as Science PI of a NASA Exoplanets Research Program grant she searches for infrared laser emissions and stellar flares in high-resolution spectra from the Habitable-zone Planet Finder on the Hobby-Eberly Telescope, and she uses the Allen Telescope Array to search for radio technosignatures. She received her undergraduate degree in physics from Carleton College in 2022.
Pinchen also works closely with Jason Wright at Penn State and Keith Vanderlinde at the Dunlap Institute.
Tri Nguyen
Tri is an NSERC Canada Postdoctoral Research Award Fellow at the David A. Dunlap Department of Astronomy & Astrophysics. He explores the nature of dark matter and its role in galaxy formation and evolution, especially at the smallest scales, developing machine learning techniques with a focus on simulation-based inference and generative models to analyze cosmological simulations and data from astronomical surveys. He was previously a CIERA Postdoctoral Fellow at Northwestern University and received his Ph.D. in Physics from the Massachusetts Institute of Technology in 2024 under the supervision of Lina Necib.
Tri works closely with Ting Li at the David A. Dunlap Department of Astronomy & Astrophysics.
Nolan Koblischke
Nolan is a Ph.D. candidate in the David A. Dunlap Department of Astronomy & Astrophysics and Data Sciences Institute Doctoral Fellow co-supervised by Jo Bovy and Chris Maddison. His research develops foundation models for search and discovery in survey astronomy. He builds tools that let astronomers query large datasets in plain language, including AION-Search, a semantic search engine over 100 million galaxy images, and ChatGaia, a conversational interface to the Gaia archive. He also asks how well AI agents can do science on their own, and led Gravity-Bench, a benchmark of physics discovery. He was previously a junior research scientist at Polymathic AI and completed his B.Sc. in Physics at the University of British Columbia in 2023.
Collaborators
Jo is a Professor and Chair of the David A. Dunlap Department of Astronomy & Astrophysics. His research focuses on understanding the dynamical structure, formation, and evolution of the Milky Way using large-scale astronomical datasets.
Ryan is an Assistant Professor and Canada Research Chair in Exoplanetary Astronomy in the Department of Physics & Astronomy at McMaster University. His research focuses on the detection and characterization of exoplanets.
Radu is a Professor in the Department of Statistical Sciences. His research focuses on Markov chain Monte Carlo methods, Bayesian computation, model selection, and applications in genetics, ecology, and astronomy.
Maria is an Assistant Professor in the David A. Dunlap Department of Astronomy & Astrophysics. Her research focuses on understanding the evolution, influence, and ultimate fate of massive stars through observations of supernovae and exotic transients.
Seiji is an Assistant Professor in the David A. Dunlap Department of Astronomy & Astrophysics. His research studies the earliest galaxies, black holes, and stars with JWST and ALMA, focusing on cosmic dawn and the first billion years of the Universe.
Renée is a Professor at the Dunlap Institute for Astronomy & Astrophysics and a CIFAR Azrieli Global Scholar. Her research focuses on theoretical and observational cosmology, including dark matter, dark energy, and the cosmic microwave background.
Vianey is an Assistant Professor in the Department of Statistical Sciences and the School of the Environment. Her research focuses on developing statistical methods for ecological and environmental data, including hidden Markov models.
Ting is an Assistant Professor in the David A. Dunlap Department of Astronomy & Astrophysics. Her research focuses on near-field cosmology, studying stars in the Milky Way and nearby dwarf galaxies to understand star formation and dark matter.
Peter is a Professor at the Canadian Institute for Theoretical Astrophysics (CITA). His research focuses on the interstellar medium, studying the gas and dust that exists between stars in the Milky Way.
Adam is an Associate Professor in the Department of Physics and Astronomy at York University. His research focuses on understanding how galaxies form and evolve, with particular emphasis on studying distant galaxies from the early Universe.
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.
Thibault is an Assistant Professor in Statistics in the Department of Computer & Mathematical Sciences at the University of Toronto Scarborough and the Department of Statistical Sciences. His research focuses on high-dimensional and nonparametric statistics, Bayesian nonparametrics, and uncertainty quantification.
Keith is a Professor at the Dunlap Institute for Astronomy & Astrophysics and the David A. Dunlap Department of Astronomy & Astrophysics. An experimental cosmologist and radio instrumentalist, he designs, builds, and operates large radio telescopes including CHIME and CHORD.
Jason is a Professor in the Department of Astronomy and Astrophysics at Penn State University. His research spans stellar astrophysics, exoplanets, and the search for extraterrestrial intelligence (SETI).
Recent Alumni
Mairead is now a joint GECO and CosmicAI Postdoctoral Fellow at the University of Virginia. She completed her Ph.D. in the David A. Dunlap Department of Astronomy & Astrophysics, where she was a Data Sciences Institute Doctoral Fellow co-supervised by Ting Li, working on galactic chemical evolution using metal-poor stars and dwarf galaxies with hierarchical modeling in close collaboration with Alex Ji at the University of Chicago.
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.
Mike is now an AI Researcher at Wayve, working on AI in industry. He was a Dunlap Postdoctoral Fellow from 2023-2025 who worked on building AI foundation models to interpret astronomical images. He led the team measuring detailed galaxy morphology in Euclid and was Technical Lead of citizen science project Galaxy Zoo. He did his Ph.D. at Oxford University with Chris Lintott and then a postdoc at the University of Manchester (UK) with Anna Scaife.
Sam is now an NSF Astronomy and Astrophysics Postdoctoral Fellow at UMass Amherst working with Kate Whitaker. She completed her Ph.D. in 2025 in the David A. Dunlap Department of Astronomy & Astrophysics under the supervision of Gwen Eadie and Josh Speagle. Her research focuses on using globular cluster populations as a probe of galaxy formation and evolution, employing Bayesian hierarchical modeling techniques.
Steffani is now an NSERC Postdoctoral Fellow at UC San Diego working with Floor Broekgaarden and Kyle Kremer. She completed her Ph.D. in 2025 in the David A. Dunlap Department of Astronomy & Astrophysics working with Maria Drout and Jeremy Webb (York University). Her research focuses on the evolution of massive stars in groups, including post-common envelope binaries and dynamical interactions in dense stellar environments. With Josh Speagle, she also developed statistical and machine learning-driven approaches to search for such systems.
Amanda is now a Banting Postdoctoral Fellow at McGill University and a member of the CHIME/FRB Collaboration. She completed her Ph.D. in 2025 in the David A. Dunlap Department of Astronomy & Astrophysics under the joint supervision of Bryan Gaensler (UCSC), Gwen Eadie, and Paul Scholz (York University). Her research interests include fast radio bursts, high-energy follow-up, and circumgalactic media, particularly in the context of astrostatistics. She previously obtained an honours BSc in mathematics and physics from McGill University in 2019.
Henry is now a Senior AI Scientist at the Canadian Imperial Bank of Commerce (CIBC). He completed his Ph.D. in the David A. Dunlap Department of Astronomy & Astrophysics under the supervision of Jo Bovy, with Josh Speagle joining as co-supervisor in 2024 through his Data Sciences Institute Doctoral Fellowship. His research applied deep learning methods including Transformers and denoising diffusions to large-scale Galactic surveys.
Antonio (Tony) was a Canadian Statistical Sciences Institute (CANSSI) Postdoctoral Fellow in the Department of Statistical Sciences, where he worked in the ART as part of a Collaborative Research Team led by Gwen Eadie developing statistical methods for the Canadian Hydrogen Intensity Mapping Experiment (CHIME). He received his Ph.D. in Physics and Astronomy from the University of Glasgow.
Aarya is now an Assistant Professor at Penn State University. She was previously a Legacy Survey of Space and Time (LSST) Discovery Alliance Catalyst Postdoctoral Fellow at the Max Planck Institute for Astronomy in Germany. She completed her Ph.D. in 2023 in the David A. Dunlap Department of Astronomy & Astrophysics under the joint supervision of Gwen Eadie and Jo Bovy. Her research lies at the intersection of astrophysics and statistics by developing novel data-driven tools that guide mathematical models of the Milky Way Galaxy.