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filler@godaddy.com
Niparo is at the forefront for UK Space Legislation and Regulations.
The UK has recently rekindled its space ambitions with the aim to make the UK Space sector a key part of the economy. At the heart of this push is the desire for a domestic launch capability and new legislation and regulations have recently entered into force with this motivation.
Niparo recently wrote a dissertation giving an overview and update to how the UKs new legislation and regulations take into account international law as well as sustainability issues.
We offer broad suggestions on ways forward for the UK space sector noting the space industry can often suffer from ‘navel gazing’ and ’greenwashing.’
Niparo was recently awarded funding from the UK Space Agency to work with Space Scotland on "Developing a Sustainable Scottish Space Sector".
This Cluster Development programme will strengthen the Scottish space ecosystem by via initiatives to reduce environmental impact, addressing workforce skills challenges, and leveraging new market
Niparo was recently awarded funding from the UK Space Agency to work with Space Scotland on "Developing a Sustainable Scottish Space Sector".
This Cluster Development programme will strengthen the Scottish space ecosystem by via initiatives to reduce environmental impact, addressing workforce skills challenges, and leveraging new market opportunities with novel sectors.
(Image credit: Jeff Williams/NASA)
The Data SlipStream is the key facility that allows integration of Earth Observation (EO) datasets and a sandpit for innovation supported by active research with commercial innovations connections.
Niparo, along with the University of Edinburgh and Resilience Constellation are responsible for building the infrastructure and developing a crucial UK academic, commercial and UKSA asset.
Niparo have been directly involved in the decision making process for the NASA/ESA/CSA James Webb Space Telescope.
Niparo CEO Dr. Nic Ross was part of the JWST Guest Observer Telescope Allocation Committee (GO TAC) for the very first full year of JWST observations - Cycle 01.
Working with colleagues and students from the EPCC at the University of Edinburgh, I have investigated the performance of Recurrent Neural Networks (RNNs) on incomplete time series data.
The research paper is published here: