Speaker |
Mike Walmsley |
|---|---|
Affiliation |
University of Manchester |
Date |
Friday, 05 May 2023 |
Time |
12:00-13:00 |
Location |
Function Space, UCL Centre for Artificial Intelligence, 1st Floor, 90 High Holborn, London WC1V 6BH |
Link |
https://ucl.zoom.us/j/97245943682 |
Event series |
DeepMind/ELLIS CSML Seminar Series |
Abstract |
Modern telescopes take far more images than astronomers could ever review – but these images are only useful if we can quantify the appearance of the galaxies they capture. Galaxy Zoo (www.galaxyzoo.org) is a citizen science project recruiting hundreds of thousands of volunteers to label the appearance of millions of galaxies. This talk will describe how we support our volunteers in this task with a pragmatic mix of DL methods. I will introduce the challenges and opportunities that come from gathering labels from volunteers, rather than paid workers. I will also describe how we use our trained models to create practical tools for them - similarity search, cluster detection, personalised anomaly recommendation – by exploring the models’ learned representations. Our final models will run as part of the pipeline for the Euclid space telescope and help astronomers understand why galaxies look the way they do. |
Biography |
Mike Walmsley an astrophysics postdoc at the University of Manchester and the lead data scientist for Galaxy Zoo. He is currently on secondment to the Private Office of the Secretary of State for Health and Social Care, using data science to inform policy responses to NHS winter pressures. He will be moving to the University of Toronto as a Dunlap Fellow in September. |