Government Advances in Statistical Programming conference, 25-26 June 2025

Gwynn Gebeyehu points us to this announcement:

CALL FOR ABSTRACTS Government Advances in Statistical Programming (GASP) 2025 Submissions Due: 5 April 2025

We invite you to submit an abstract for the next Government Advances in Statistical Programming (GASP) conference scheduled for 25-26 June 2025, 12-5 pm ET. There is no fee to present or attend the conference. The virtual conference is open to anyone and will feature various ways for you to share your work:

Regular presentation: Regular presentation sessions will include several talks with a common theme. Each speaker will have about 12-15 minutes followed by Q&A.

Lightning talk: Quick 5-7 minute presentation on a particular application, code, visualization, etc. Lightning talks will be grouped into a session and presented back-to-back, with most Q&A delayed until the end.

Students: Separate lightning talk sessions may be set up for students (e.g., using government data, code demonstrations, or data visualizations of government activities).

Other: A panel, an unconference session, workshop, demo, or interest group meeting. To submit an abstract, complete this google form. If you have questions, contact Lisa Frehill (lisa.frehill@hq.doe.gov) or Peter Meyer (meyer.peter@bls.gov).

We welcome any submission of interest to a general audience of producers and users of government statistics. For example, past conferences have included the following topics:

Tools and techniques • Open source software (Python, R, Stan, Julia) • Natural language processing • Machine learning / Neural networks • Data analytics • Generative AI / Large Language Models (LLMs)

Infrastructure – resources • Version control / reproducibility • Developing R libraries / Python packages • Cost-saving innovation • Privacy and disclosure avoidance • Policy issues (e.g., open government) • Porting code

Deployment • Dashboards (e.g., Shiny) • Data visualization • Innovation in data dissemination and accessibility

Applications • Proof of concept • Model development, selection, and validation • Automating and streamlining analysis

Selected GASP23 papers appeared in a special issue (July 2024) of the Journal of Data Science. The GASP23 Final Program can be accessed here.

Sponsored by: Data Science for Federal Statistics (DSFS), an Interest Group of the Federal Committee on Statistical Methodology (FCSM)