Study MSc AI & Space Technology

Latest News

  • Space 2050: Professor Paul Febvre's masterclass and Cantor Technology Lecture Professor Paul Febvre of Cranfield University spent a day at Bradford, with a masterclass in the afternoon and a Cantor Technology Lecture on the future of space to a full Small Hall in the evening.
  • Space comes to Bradford: Professor Paul Febvre on the future of space On Wednesday 21 October, Professor Paul Febvre of Cranfield University gave a masterclass and the Cantor Technology Lecture, "Space 2050: Opportunity, Sustainability and the Future of Life Beyond Earth".
  • Exploring new Space AI collaborations with Space Hub Yorkshire and York St John University The Centre welcomed David Brady from Space Hub Yorkshire and Dr Rashmi Siddalingappa from York St John University London Campus to explore joint work in Space AI research, education and outreach.
  • Keynote at IEEE ICERAI 2026: how AI is transforming healthcare, space and security Prof. Rami Qahwaji gave one of four keynote addresses at ICERAI 2026, hosted by the American University of Ras Al Khaimah, which brought together 278 researchers from 24 countries.
  • New paper: predicting significant solar flares with bidirectional LSTMs A new paper by Bamidele Moses Akinwumi and Rami Qahwaji shows that following how each sunspot region's magnetic field changes over 72 hours helps predict major solar flares, and makes the dataset freely available.
  • ASAP's development was submitted as an Impact Case study for REF 2021 and was rated as 100% Internationally Excellent (3*)
  • ASAP is now integrated with NASA's CCMC Flares Scoreboard. Please check: CCMC's website
  • Rami Qahwaji was invited to deliver a keynote speech at the 1st Int Conf on Synergizing Health, AI, and Pedagogical Excellence & Enterprise (Dec 2025), discussing AI deployments across different disciplines
  • Prof. Rami Qahwaji delivered an invited keynote speech at the Digital Excellence Forum, organised by the UAE Department of Government Enablement in Abu Dhabi (Feb 2025), examining international strategies for responsible and effective AI adoption
  • Rami delivered an Invited talk at COSPAR2024's session on “Applications of ML in Solar and Heliospheric Physics”, in Busan (South Korea), entitled “AI Techniques for Processing Solar and Space Data”
  • Prof. Rami Qahwaji was also an invited speaker at a session organised by the World Technology Universities Network on the WEHE Nexus initiative in 2024. His talk was entitled “Space Technologies & AI for Environmental Monitoring”.
  • Prof. Rami Qahwaji was an invited speaker at the SatNEx V School, sponsored by ESA and hosted at University of Bradford in November 2023. His presentation, “Applications of AI in Space Mission and Space Weather Events”, was delivered to postgraduate students and researchers from across Europe.

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Welcome to Our Research Group

We lead research in processing multiwavelength solar and space imagery, developing advanced visual computing and AI algorithms for applications such as space weather prediction and beyond.

Operational Credibility ASAP integrated in real-time with NASA's CCMC Flares Scoreboard
Academic Excellence ASAP rated 100% Internationally Excellent (3*) as REF2021 Impact Case study
Future-Focused continuously advancing our methods with latest AI
Global Leadership invited keynote addresses at major int. conferences

Live Solar Observatory

ASAP solar flare predictions

ASAP 24-hour solar flare prediction

Last Space Weather data- Source: NOAA/SWPC

HMI Continuum Image from SDO

HMI Magnetogram Image from SDO

How our AI predicts solar flares

01 Solar imagery SDO/HMI continuum & magnetogram images
02 Sunspot detection Morphological image processing finds candidate regions
03 Classification Neural networks assign McIntosh classes to each group
04 Machine learning Trained on decades of flare & sunspot catalogues
05 Flare probability Real-time C-, M- and X-class flare forecasts
Explore the full ASAP pipeline

Current Space Weather

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R1–R2 blackout probability today (M-class flares): – R3+ probability (X-class flares): –

Live data from NOAA Space Weather Prediction Center