(沈佳士)
Statistical AI for Cosmic Discovery
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.
Email: j.speagle@utoronto.ca
Office: UY 9134 (Statistical Sciences) and AB 206 (Astronomy & Astrophysics)
Where stars meet statistics
I am incredibly fortunate to co-lead the interdisciplinary Astrostatistics Research Team (ART) along with its founder Gwen Eadie.
Pioneering new methods in astrophysics at the intersection of statistics and AI
Interdisciplinary team spanning astrophysics, statistics, and data science
My research focuses on four main areas:
Developing novel methods to discover underlying patterns from (many) large, messy datasets.
Building up a rigorous understanding of how statistical methods work both in theory and in practice in order to extract novel scientific insights.
Establishing robust frameworks and designing tractable algorithms to efficiently quantify how much we can learn from data.
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.
This work often involves working with massive datasets from wide-field imaging and spectroscopic surveys containing observations ranging from billions of stars and galaxies to interstellar gas and dust, but can also include smaller datasets from targeted observations of individual objects along with everything in between.
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.
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.
Bachelor's Degree with Honors in Astrophysics and Physics at Harvard University. Participated in multiple research projects across astronomy.
Worked with Alexie Leauthaud and Kevin Bundy at Kavli IPMU. Began shifting my focus to astrostatistics and data science.
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.
Banting Fellow and Dunlap Fellow at University of Toronto, working with Gwen Eadie.
While on leave from UofT, worked as a Research Scientist at River Run Trading on cutting-edge quantitative trading strategies for crypto assets.
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.