For online registrations visit⏩: rss.org.uk/training-eve...

To register for attending in-person visit⏩: rss.org.uk/training-eve...

Presentations:
- Sonali Parbhoo: Causal Machine Learning for Actionable Insights in Healthcare
- Simone Padoan: Bayesian inference for tail risk extrapolation in time series
- Vasiliki Koutra: Designing experiments on networks

Articles selected at the call by Emily B. Dennis and coauthors, Elisabeth Bersson and Peter D. Hoff, and Jonathan Koh and Thomas Opitz, address the most important present issues when analyzing such datasets.

These opportunistic datasets can be substantially large and present many statistical challenges in terms of sparse and missing data, issues with data collection (e.g. reporting bias and spatial bias) and computational challenges.

Citizen science involves volunteers who participate in scientific research by collecting data, monitoring sites, or taking part in the whole process of scientific inquiry.

We particularly welcome applications from early career academic or industry statisticians from different disciplinary backgrounds.

We hold one online committee meeting roughly every four months and one AGM per year, and normally organise 2-3 events a year, including webinars and sessions at the RSS conference and other conferences.

If you would like to be considered send an email (subject line “Emerging Applications Committee 2025”) to the Secretary (ruth.salway(at)bristol(.)ac(.)uk) by 5pm on 30th September 2025, with a short paragraph on your background, reason to join, and what you will contribute.

We are looking for enthusiastic individuals who are keen to contribute new ideas for meetings and events, and willing to take on one of the committee roles. The EAS offers a forum for statistical applications that do not fall into the remit of other sections.