Archangel Imaging
João Neto has work experience in various roles and companies.
In 2012, they worked at Spectrum as a Mentor. João held this position from November 2012 to November 2014.
From 2019 to 2022, they were employed at the Mercedes-AMG Petronas Formula One Team as a Software Engineer. In this role, they were responsible for maintaining the F1 Performance stack, implementing new features, and leading the concept, design, and implementation of a new product. João also had direct contact with end-users for requirement gathering and validation.
Currently, João works at Archangel Imaging as a Simulation Engineer, starting in October 2022.
Overall, João Neto has a solid background in software engineering and has worked in different industries, gaining expertise in various areas.
João Neto began their education in 2009 at Escola Secundária Alves Martins, where they completed their 12º Ano in Ciências e Tecnologia in 2012. João then pursued higher education at Faculdade de Engenharia da Universidade do Porto from 2012 to 2017, earning a Master's degree in Computer Software Engineering. Building upon their previous academic achievements, João enrolled in the same institution from 2017 to 2018 to pursue a Doctor's degree in Artificial Intelligence.
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Archangel Imaging
Archangel Imaging provides software and hardware options to make machines smart enough to become team mates you can trust to do their part, rather than tools you need to constantly manage. Veteran founded and owned we focus on supporting users in remote, exposed on challenging environments, including police, service personnel, first respondersand NGOs. We’re active in both the UK and US. Hybrid human-machine teams will be much more effective in protecting assets, people & planet at scale. For that to happen, we need our technology to be able to operate without depending on human attention or on vulnerable infrastructure. We specialise in advanced artificial intelligence (AI) for cameras and GNSS-denied navigation for manned and unmanned systems. Real time remote monitoring is difficult to achieve with people alone. The areas are often huge and distant, meaning hard-working maintenance, security or safety staff have poor coverage with long response times. Pipeline security, anti-poaching, asset integrity monitoring and border patrol are a few examples. Whilst we (humankind) have developed an impressive array of technologies, including drones and ground sensors, these remain tools to use at long range. These tools are dependent on: 1) human attention to make best use of them and 2) infrastructure to support them, with communications and positional information in particular. GPS has become increasingly easy to jam and to spoof. Not only that but the orbital infrastructure itself is at direct risk of vandalism.Archangel Imaging provides a complimentary solution stack to enable human-machine team work in the real world. These make machines smarter, more resilient in a changing situation and easier to work with in a human workflow. Xnaut AI co-pilots enable existing uncrewed drones, boats and rovers to make mission level navigation decisions based on live observed context. Designed to work when GPS is being spoofed or jammed, Xnaut GENIE Uniquely combines over 50 navigation methods to ensure reliable, resilient and accurate location data is provided to the system's autopilot. Argonaut smart cameras have been designed to operate independent of infrastructure. The camera and tower products are fully self-contained, with power, communications, sensors and compute. Cerebella human-machine teaming mission management software integrates diverse machines into people-centred geospatial workflows.