Aug 6-11, 2022

Astrostatistics sessions at JSM

Note: all times are in EDT, Eastern Daylight Time (GMT+4)

INDEX

AIG meeting | Student Paper Award

Advances in Astrostatistics in the Great White North | Astrostatistics: Innovative Statistical Methods for Foundational Astrophysical Sciences | Open Problems in Astrostatistics | Other events

We will use an Astrostatistics Interest Group Slack channel (opens in a new tab) to ease communication between the audience and the speakers at the various sessions. In order to be added to this channel, please contact one of the office bearers or write to aigamstat @ gmail.

AIG Business Meeting

Wednesday Aug 10 2022, 2:30pm-4:00pm EDT

The annual AIG Business Meeting will be held in the Scarlet Oak Room at the Marriott Marquis. Details for joining remotely will be provided by email to AIG members.

JSM Astrostatistics Slack Channel

To see news and announcements regarding JSM and the astrostatistics sessions, or to simply ask questions, go to this Slack workspace (opens in a new tab) and go to the #jsm2022 channel.

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Session 222043

Tuesday Aug 9 2022, 2:00pm-3:50pm EDT

Advances in Astrostatistics in the Great White North (opens in a new tab) -- Invited Papers

SSC (Statistical Society of Canada), Canadian Statistical Sciences Institute, Section on Physical and Engineering Sciences
Organizer(s): David C Stenning, Simon Fraser University
Chair(s): David C Stenning, Simon Fraser University

2:05 pm: Light from the Darkness: Detecting Ultra-Diffuse Galaxies in the Perseus Cluster Using Log-Gaussian Cox Process (opens in a new tab)
Dayi (David) Li, University of Toronto
2:30 pm: Mapping the Milky Way in 5-D with Big Data (opens in a new tab)
Joshua Shen Speagle, University of Toronto
2:55 pm: Statistical Challenges in Gravitational Wave Astrophysics (opens in a new tab)
Mervyn Chan, The University of British Columbia
3:20 pm: Discussant
Derek Bingham, Simon Fraser University
3:45 pm: Floor Discussion

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Session 223140

Wednesday Aug 10 2022, 10:30am-12:20pm EDT

Astrostatistics: Innovative Statistical Methods for Foundational Astrophysical Sciences (opens in a new tab) -- Topic Contributed Papers

Korean International Statistical Society, Section on Physical and Engineering Sciences, Astrostatistics Special Interest Group
Organizer(s): Hyungsuk Tak, Pennsylvania State University
Chair(s): Hyungsuk Tak, Pennsylvania State University

10:35 am: Using Topological Data Analysis to Distinguish Cosmological Models of Our Universe (opens in a new tab)
Jessi Cisewski-Kehe, University of Wisconsin-Madison
10:55 am: Model Validation and Estimation of Mass-Radius-Flux Distribution for Exoplanets Under Heterogeneous Measurement Errors (opens in a new tab)
Sujit Ghosh, North Carolina State University; Qi Ma, Facebook Inc
11:15 am: When Geometry and Statistics Meet Cosmology: The Challenge of Detecting Cosmic Webs (opens in a new tab)
Yen-Chi Chen, University of Washington; Yikun Zhang, University of Washington
11:35 am: Likelihood-Free Frequentist Inference for the Physical Sciences (opens in a new tab)
Luca Masserano, Carnegie Mellon University; Ann Lee, Carnegie Mellon University; Mikael Kuusela, Carnegie Mellon University; Rafael Izbicki, Federal University of São Carlos
11:55 pm: Discussant
Jogesh G. Babu, Pennsylvania State University
12:15 am: Floor Discussion

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Session 223148

Wednesday Aug 10 2022, 10:30am-12:20pm EDT

Open Problems in Astrostatistics (opens in a new tab) -- Topic Contributed Papers

Section on Physical and Engineering Sciences, Astrostatistics Special Interest Group, Section on Bayesian Statistical Science
Organizer(s): Yang Chen, University of Michigan
Chair(s): Yang Chen, University of Michigan

10:35 am: Calibrated Uncertainty Quantification with Application to Galaxy Photometric Redshifts (opens in a new tab)
Ann Lee, Carnegie Mellon University
10:55 am: Topics for Statistical Advances for Use in Astronomy (opens in a new tab)
Herman Marshall, MIT
11:15 am: Exploring the Quantification of Uncertainty in the Analysis of Multi-Dimensional High-Energy Astronomical Data Sets (opens in a new tab)
Aneta Siemiginowska, Center for Astrophysics | Harvard & Smithsonian
11:35 am: Discussant
David van Dyk, Imperial College London
11:55 pm: Discussant
Vinay Kashyap, Center for Astrophysics | Harvard & Smithsonian
12:15 am: Floor Discussion

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Session 223135

Thursday Aug 11 2022, 10:30am-12:20pm EDT

Astrostatistics Interest Group: Student Paper Award (opens in a new tab) -- Topic Contributed Papers

Information about Student Paper competition

Astrostatistics Special Interest Group
Organizer(s): Yang Chen, University of Michigan
Chair(s): Peter E. Freeman, Carnegie Mellon University

10:35 am: Functional Data Analysis for Extracting the Intrinsic Dimensionality of Spectra: Application to Chemical Homogeneity in the Open Cluster M67 (opens in a new tab)
Aarya Anil Patil, University of Toronto
10:55 am: Supervised Learning and Hierarchical Bayesian Modeling Under Covariate Shift in Supernova Cosmology (opens in a new tab)
Maximilian Autenrieth, Imperial College London
11:15 am: The Mass of the Milky Way from the H3 Survey (opens in a new tab)
Jeff Shen, University of Toronto
11:35 am: Testing the Consistency of Dust Laws in SN Ia Host Galaxies: A BayeSN Examination of Foundation DR1 (opens in a new tab)
Stephen Thorp, Institute of Astronomy, University of Cambridge
11:55 am Photometry on Structured Backgrounds: Local Pixelwise Infilling by Regression (opens in a new tab)
Andrew Kahlil Saydjari, Center for Astrophysics | Harvard & Smithsonian
Winner of Student Paper Competition
12:15 am: Floor Discussion

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Other events of interest

The following sessions and events feature methodological and applied work that may appeal to those working with astronomical data:

Sunday:

Session 7: Advances in Multivariate Spatial Process Modeling for Environmental Data (opens in a new tab)
Session 32: Nonparametric Methods with High-Dimensional Data (opens in a new tab)
Session 39: Advances in Time Series: Statistics Meets Machine Learning (opens in a new tab)
Session 40: Modern and Innovative Spatial Methods in Ecology and the Environment (opens in a new tab)
Session 64: Computational Advances in Bayesian Inference (opens in a new tab)

Monday:

Session 91: Spatial Statistics and UQ: Foundations for Innovation in Environmental Science (opens in a new tab)
Session 103: Uncertainty Quantification for Machine Learning (opens in a new tab)
Session 115: Advances in Clustering and Classification (opens in a new tab)
Session 126: Topics at the Frontier of Statistical Computing and Machine Learning (opens in a new tab)
Session 150: Methods and Computing for Spatial and Spatio-Temporal Data (opens in a new tab)
Session 180: Machine Learning and Artificil Intelligence: Uses and Misuses! (opens in a new tab)

Tuesday:

Session 244: Advances in Statistical Machine Learning (opens in a new tab)
Session 270: Advanced Multivariate Time Series Modeling (opens in a new tab)
Session 282: Sampling and Ensembling in Statistical Computing (opens in a new tab)
Session 283: Deep Learning Methods (opens in a new tab)
Session 308: Highlights in Bayesian Analysis: Innovations in Bayesian Learning (opens in a new tab)
Session 333: Advances in Bayesian Modeling (opens in a new tab)

Wednesday:

Session 363: Should Science Abandon Statistical Significance? (opens in a new tab)
Session 381: Recent Advances in High-Dimensional EStimation and Inference Methods (opens in a new tab)
Session 403: Research Advances at the Interface of Uncertainty Quantification and Machine Learning for High-Consequence Problems (opens in a new tab)
Session 404: Gaussian Process Models Over Non-Euclidean Domains (opens in a new tab)
Session 408: Recent Advances in Statistical Machine Learning (opens in a new tab)
Session 424: Priors and Model Specifications for Variable and Feature Selection (opens in a new tab)
Session 458: Bayesian Methods in Spatial Statistics (opens in a new tab)

Thursday:

Session 500: Invited Papers: Journal of Statistical Analysis and Data Mining (opens in a new tab)
Session 504: Computational Challenges in Modern Statistical Inference (opens in a new tab)
Session 521: Statistical Methods for Functional Data (opens in a new tab)
Session 533: Prediction and Inference in Statistical Machine Learning (opens in a new tab)
Session 560: Latent Space Modeling and Dimensionality Reduction (opens in a new tab)