Topic: Computing
Session Title: Beyond Astronomy: Applying techniques and software from astronomy to solve problems here on Earth
Description:
This session is for astronomers who are applying techniques and software used in astronomy to solve problems here on Earth. This could take the form of image processing at any wavelength, analysis of spectra, or applications to data science. For example, the detection of interesting features in remote sensing or medical imaging. Machine learning techniques adapted for astronomy and then applied elsewhere are welcome. This could take the form of astronomers wanting to generate impact for funding cases or the REF. We are also interested to hear from those who are involved in spinning out and/or commercialising their projects.
The talks need not even focus on the techniques themselves and could describe the successes and difficulties encountered when breaking into new fields or the commercial sector. The aim is to make this session as broad as possible as it would be great to see what astronomers are involved in when not looking up.
We expect this session to be valuable to early career astronomers who may be interested in exploring the applications of their research within or outside of an academic career, and anyone looking to diversify their funding opportunities or generate impact.
Organiser(s): John Stott, Jim Geach, Brooke Simmons, Mat Smith, Sonny Bailey, Kevin Pimbblet, Alyssa Drake
Schedule:
Venue: WILB-LT02
Session 1: Monday 15th July, 09:00 – 11:00
Name | Time | Title |
Kevin Pimblett | 09:00 | Detection of Deepfakes using Astronomy Techniques |
James Trayford | 09:20 | Ear to the Sky: sonification of data as a new data method in astronomy and beyond |
Brooke Simmons, Danil Kuzin, Lydia Makrygianni, Alice Mead, The Zooniverse Team | 09:40 | Lessons Learned from Applying Astrophysical Methods to Disaster Relief, and Vice-Versa |
Reece Wilkinson | 10:00 | Commercial potential of the Object Classification Tools for Astronomy VIsUaliSation (OCTAVIUS) |
Michael J. Smith, Ryan J. Roberts, Eirini Angeloudi, Marc Huertas-Company | 10:20 | Scaling Large Observation Models for Astronomy and Applying it to Earth-Observation |
Hugh Dickinson | 10:40 | Rapid prediction of lab-grown tissue properties using Deep Learning |