AI for Smarter Telescopes: UK Uni Breakthroughs | AcademicJobs
Explore how UK universities like Oxford and Manchester are using AI to make telescopes smarter, from supernovae detection to SKA data processing.
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Dr Fiorenzo Stoppa is a Royal Society Newton International Fellow in the Department of Physics at the University of Oxford. He works in astrostatistics and astroinformatics as part of Professor Stephen Smartt’s group, with a focus on end-to-end processing for wide-field, time-domain optical surveys. His research develops methods and tools that convert raw astronomical images into science-ready products, covering calibration, astrometry, reliable object detection, classification, cross-matching, alerting and spectral analysis. He works primarily with data from MeerLICHT, BlackGEM, ATLAS and Pan-STARRS, and contributes to the Lasair broker for alerts from the Rubin Observatory’s Legacy Survey of Space and Time.
Current projects include leading the ASTA system for automated detection and characterisation of satellite trails in wide-field optical images, using annotated MeerLICHT data and a Probabilistic Hough Transform to produce pixel-level masks that protect source detection and photometry. He also develops and maintains SNID-SAGE, a Python toolkit for spectral analysis of astronomical transients that extends the classic SNID cross-correlation method with an interactive interface, clustering-aided suggestions and LLM-assisted workflows. Additional work examines how multimodal large language models can support or replace stages in survey pipelines for real-bogus filtering, light-curve analysis and spectra characterisation, producing interpretable textual outputs for alert brokers and follow-up processes.
Explore how UK universities like Oxford and Manchester are using AI to make telescopes smarter, from supernovae detection to SKA data processing.