Nano-satellites are a very popular trend in satellite design right now: many small low-powered satellites are built using commodity components rather than the traditional approaches that incorporate high-specced parts in the construction of larger satellites. This greatly reduces their cost and has enabled a new generation of applications, particularly through the deployment of “constellations”: groups of satellites operating in tandem to monitor phenomena such as climate change and protect against impending natural disasters.
David and Earl will be working with industrial experts at space companies Craft Prospect
and Bright Ascension
, alongside the University of Manchester. Their focus will be on the application of Deep Learning and Code Optimisation methods to the satellite software, taking advantage of emerging hardware platforms that offer enhanced capabilities on-board.
“In the same way that commodity hardware components revolutionised satellite construction, we believe there is potential for a revolution in the software domain,” said David, who will take responsibility for algorithm development on the project.
By applying the power and commoditised tools of machine learning that have emerged over the last decade, the researchers intend to make the satellites more autonomous, reducing the demands on the data connection to the ground station. The work will involve a combination of cutting-edge Machine Learning methods alongside the improvement of industry-standard software through methods such as Genetic Improvement.
“We’re excited to see how far we can take this,” says White, “The timing is perfect for a new wave of satellite applications enabled by AI.”
DAASE research group MaJiCKe have moved to work with Facebook in London. MaJiCKe have developed software that uses Search Based Software Engineering (SBSE) to help engineers find bugs while reducing the inefficiencies of writing test code. Their product Sapienz automatically generates test sequences using SBSE to find crashes using the shortest path it can find. Sapienz is the world’s first automated test tool able to minimise the length of tests which simultaneously maximising the amount of code checked.
“We are very excited to have this outstanding opportunity to achieve real world impact for UCL’s excellent software engineering research”
Professor Mark Harman
The MaJiCKe team comprise Professor Mark Harman – Scientific Advisor, Yue Jia – CEO and Ke Mao – CTO from the department of Computer Science at University College London (UCL). Professor Harman cofounded the area of SBSE in 2001.
“We provide an atmosphere to nurture collaborations with industry, its great to see a team like this taking their world leading expertise to Facebook”
Jane Butler, UCL Engineering Vice Dean
All at DAASE wish Mark, Yue and Ke the very best of luck and look forward to hearing all about their contribution to Facebook’s goal of connecting the world.
Yuanyuan Zhang, senior research associate on the DAASE project describes her research in software testing, Natural Language Processing and model inference.