Statistical Learning & AI
Developing novel methods to discover underlying patterns from (many) large, messy datasets.
Astrostatistics · University of Toronto
Joshua S. Speagle沈 佳 士
Combining astronomy, statistics, and AI to understand how stars and galaxies form, behave, and evolve.
Who I am
Astrostatistics at the University of Toronto
I am an Assistant Professor of Astrostatistics jointly appointed between the Department of Statistical Sciences and the David A. Dunlap Department of Astronomy & Astrophysics at the University of Toronto. I am also an Associate Member of the Dunlap Institute for Astronomy & Astrophysics as well as a Member of the Data Sciences Institute.
What I do
Four research areas
I develop statistical & machine-learning methods and apply them to the largest astronomical surveys — from billions of stars and galaxies down to individual objects.
Interpretability & Insight
Building up a rigorous understanding of how statistical methods work both in theory and in practice in order to extract novel scientific insights.
Inference & Computation
Establishing robust frameworks and designing tractable algorithms to efficiently quantify how much we can learn from data.
Discovery & Understanding
Applying these methods to large-scale astronomical surveys to uncover new insights about the universe, with a focus on how galaxies like our own Milky Way form, behave, and evolve over time.
The team
The Astrostatistics Research Team
Where stars meet statistics
I am incredibly fortunate to co-lead the interdisciplinary Astrostatistics Research Team (ART) along with its founder Gwen Eadie.
Cutting-Edge, Interdisciplinary Research
Pioneering new methods in astrophysics at the intersection of statistics and AI
Collaborative, Inclusive Environment
Interdisciplinary team spanning astrophysics, statistics, and data science
Join us
Collaboration & Mentorship
I consider collaboration and mentorship to be at the heart of my research and love working with students, postdocs, visiting researchers, and faculty across disciplines. If you're interested in working with me on a short-term or long-term project, please don't hesitate to reach out.
Postdoctoral Researchers
Gwen and I are always looking for enthusiastic postdoctoral researchers to join the Astrostatistics Research Team! If you are interested in applying your skills to cutting-edge research in astrostatistics, please feel free to reach out to either me and/or Gwen.
Fellowship opportunities: CPRA · CANSSI CDPF · CANSSI Ontario · Arts & Science · Research Excellence · Provost · Dunlap · CITA · DSI · Schmidt AI in Science
Graduate Students
I am always looking for enthusiastic students to join our research group. While I cannot directly admit graduate students, I encourage applications to our Master's/Doctoral programs. Please feel free to reach out if you are interested in learning more about my research and how it might fit into your potential graduate studies.
University of Toronto Undergraduates
I love working with University of Toronto undergraduate students both throughout the year and over the summer. I often post opportunities through existing program streams to ensure equitable review processes.
Canadian Undergraduates
For Canadian undergraduate students, there are several excellent summer research programs available. These competitive programs provide structured research experiences with funding support.
International Undergraduates
Several funded programs exist for international students to conduct research at Canadian universities. Eligibility varies by country of origin and program.
Visiting Researchers & External Collaborators
I am always happy to start up new collaborations or strengthen existing ones. If you are interested in coming to the University of Toronto for either a short visit or extended stay, please reach out so we can discuss potential projects and coordinate funding.
Equity, Diversity, and Inclusion
We strive to create an environment where diverse backgrounds are an integral and well-supported part of our research community as well as individual members' identities as researchers. All members should know they are always valued.
Open and Accessible Science
We're committed to growing our community by engaging in reproducible research, releasing open-source tools and pedagogical materials, and mentoring the next generation of astrostatisticians and data scientists through hands-on learning.
Short biography
Short Biography
1990s - 2011
Childhood
USA & China
Shuttled between the US (around Milwaukee) and China (Beijing and Shanghai). Fell in love with astronomy at age 17 after reading From Eternity to Here by Sean Carroll.
2011 - 2015
Undergraduate
Boston, Massachusetts
Bachelor's Degree with Honors in Astrophysics and Physics at Harvard University. Participated in multiple research projects across astronomy.
2015 - 2016
Project Academic Support Staff
Kashiwa, Japan
Worked with Alexie Leauthaud and Kevin Bundy at Kavli IPMU. Began shifting my focus to astrostatistics and data science.
2016 - 2020
Graduate School
Boston, Massachusetts
Master's and Doctoral Degrees at Harvard. Thesis: "Mapping the Milky Way in the Age of Gaia" under Doug Finkbeiner, Charlie Conroy, and Daniel Eisenstein, with additional supervision by Alyssa Goodman.
2020 - 2022
Postdoctoral Fellow
Toronto, Canada
Jan-Apr 2025
Research Scientist
Toronto, Canada (Remote)
While on leave from UofT, worked as a Research Scientist at River Run Trading on cutting-edge quantitative trading strategies for crypto assets.
2022 - Present
Assistant Professor
Toronto, Canada
Joint appointment in Statistical Sciences and Astronomy & Astrophysics. Co-leading the Astrostatistics Research Team (ART) with Gwen Eadie.
Outside of work, I mostly enjoy hanging out at home or going out with my wife, our two dogs, and our son. I also watch way too much anime, play way too many video games, and have a supremely unhealthy love of junk food and soda.