Abstract Number:
1727
Submission Type:
Topic-Contributed Paper Session
Participants:
David Stenning (1), David Stenning (1), Kelly Moran (2), Ky Potter (3), Joshua Speagle (4), Samantha Berek (2), Amanda Cook (5)
Institutions:
(1) Simon Fraser University, N/A, (2) N/A, N/A, (3) Simon Fraser University & Los Alamos National Laboratory, Canada, (4) University of Toronto, N/A, (5) McGill University, N/A
Chair:
Session Organizer:
Speaker(s):
Kenzie Potter
Simon Fraser University & Los Alamos National Laboratory
Session Description:
Advances in astrophysics and space sciences increasingly rely on innovative statistical methodology, which in turn is increasingly developed by Canadian or Canada-affiliated researchers. Canada is fast emerging as a leader in astrostatistics research, broadly defined, with world-class universities and research institutes, and unique resources such as the Canadian Astronomy Data Centre and the Canadian Hydrogen Intensity Mapping Experiment. This session will include four speakers, all of whom are affiliated with Canadian universities. They will discuss a variety of recent and exciting astrostatistics contributions, including, but not necessarily limited to: scalable Gaussian processes for modeling heteroskedastic spacecraft data; statistical signal processing for separating routine and anomalous ionospheric density fluctuations measured from the International Space Station; modeling globular cluster systems using hurdle models, errors-in-variables models, and zero-inflated count models; and trustworthy simulation-based inference methodology for astrophysical data. The talks will highlight how challenges in astrophysics and space sciences spur advances in statistical methodology, and how Canada is a leader in such interdisciplinary research.
Speakers and Tentative Presentation Titles:
Kelly Moran (Los Alamos National Lab and Simon Fraser University): Statistical methods for separating routine and anomalous ionospheric density fluctuations
Ky Potter (Simon Fraser University and Los Alamos National Lab): Scalable Gaussian processes for modeling heteroskedastic spacecraft data
Sam Berek (University of Toronto): Understanding star formation on the largest scales using the smallest galaxies: a statistical approach
Josh Speagle (University of Toronto): Uncertainty Quantification and Calibration in Stellar Parameter Estimation
Sponsors:
Section on Physical and Engineering Sciences 2
Section on Statistical Learning and Data Science 3
SSC (Statistical Society of Canada) 1
Theme:
Communities in Action: Advancing Society
No
Applied
Yes
Estimated Audience Size
Small (<80)
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2026. The registration fee is nonrefundable.
I understand