Dr. Neil Vaughan recieved 1st BSc (Hons) Computer Science in 2006 from Brunel University (est. 1966) in London. Working within Department of Information Systems and Computing, now named Department of Computer Science ranked top in the country for ‘Research Power' in the 2008 Research Assessment Exercise (RAE). His research on robotic pathfinding, computer vision, neural networks, and evolutionary algorithms won the Best Written Work Prize 2006. His research on face and hand recognition in computer vision won Best Final Year Project 2006. He recieved the honorary 2006 Brunel University Prize for outstanding academic excellence.
In 2006 Neil Vaughan worked for LogicaCMG (Now acquired by CGI group). As contractor for Ministry of Defence (MOD) designing SQL and data structures for Defence Medical Information Capability Programme (DMICP) migrating legacy health record data from RAF personnel held on disparate computers in over 500 worldwide MOD medical data facilities. In 2007, working at Galileo for European Space Agency (ESA) where he designed security facilities and encryption key programming in java. In 2008, Neil Vaughan worked on orbital satellite positioning GPS tracking for Galileo satellite. Neil travelled to Frascati, Italy in 2009, where he presented successful multinational funding bids to ESA headquarters, winning new contract. His work at the UK Parliamentary and Health Service Ombudsman focussed on NHS data-driven analytics. In 2009 Neil Vaughan was lead developer for data driven website ConsumerDirect, now in National Archives, part of Office of Fair Trading a government funded data-driven center, now acquired by Citizens Advice
Dr. Neil Vaughan began his PhD at Bournemouth University in 2010. Research developed novel virtual reality for patient-specific epidural training. His clinical trial at Poole Hospital recieved NRES Ethics approval to measured novel needle insertion pressure data from obstetric patients.Working within School of Design, Engineering and Computing, now Faculty of Science & Technology Dr Vaughan's PhD research was awarded the 2014 Postgraduate Research Prize by the Vice-chancellor of Bournemouth University, as the winning research project across all schools and faculties delivering most impact and progress judged be the Executive Committee. Winner of the worldwide title IET Innovation Awards 2013, Neil Vaughan's research beat British Telecomms Research Laboratory in the grand final, beating over 400 entries from 92 countries, winning the ICT category open to all HEI and industry research worldwide - this recieved numerous press, news and magazine coverage. Neil Vaughan was winner of the competitive IET Scholarship award 2013, open to all PhD students in the country. Neil Vaughan was honored with title of UK ICT Pioneer, shown on BCS video winning against all PhD students in the country, winner of 'Transforming Society' award, beating Oxford, UCL, Imperial in the grand final which culminated in a high profile showcase where Neil Vaughan presented his dragons den pitch to CEO of EPSRC, and key stakeholders IBM, ARM, Defence science and technology laboratory (dtsl), Hewlett Packard (HP), BCS, The Chartered Institute for IT. Dr Vaughan's research was finalist in top ten for Times Higher Education (THE) Awards 2014 for ICT, against all UK universities. His research was selected in final 8 for the UK National Patient Safety Awards 2013. The only european finalist in the top ten worldwide for the Innovation Showcase (IShow) by American Society of Mechanical Engineers (ASME), alongside MIT, Harvard, John Hopkins Universities.
As post-doctoral researcher at Bournemouth University (Awarded the Queens Anniversary Prize 2011) within Faculty of Science & Technology, Neil Vaughan developed novel Java Smartphone Apps for interfacing with NHS medical devices. In 2015 his research has involved developing virtual reality simulators for a range of medical procedures. Working with data analytics Dr. Vaughan has analysed medical MRI and Ultrasound images. Using a trained neural network Dr. Vaughan applied data from 23088 USA patients to predict the body shape of various BMI patients.