Dr Feng Gu
School/Department: Computer Science & Mathematics
Position: Research Associate
I am currently a research associate in computer vision for ambient assisted living (AAL), at Kingston University, London, for the BREATHE project that aims to deliver a technological platform which provides daily guidance and support for the informal caregiver in the long-term care of elderly people or people with cognitive disabilities. My expertise brings novel techniques in both computer vision and machine learning to AAL applications.
After obtaining a BSc. in Computer Science at Harbin Engineering University, China, in 2004, I attended the University of Warwick, UK, and was awarded a MSc. in Engineering in 2006. In 2007, I started my PhD research in bio-inspired computing for data mining at the Intelligent Modelling & Analysis Research Group (IMA) the University of Nottingham, and obtained a PhD in Computer Science in 2011. During my PhD, I was employed as a short-term research fellow at Poznan University of Technology, working on the Marie-Curie Early Stage Training in Bioinformatics Optimisation (BIOPTRAIN) project. I also developed an online database management system for the WildTech project, regarding novel technologies for the surveillance of wildlife infections.
After my PhD, I was subsequently empolyed as a post-doctoral research fellow in cognitive vision at University of Leeds, working on the Mind's Eye project funded by DARPA, in collabration with researchers from Standford Research Institute (SRI) international and University of Maryland. In addition, I was involved in the COGNITO project, regarding cognitive workflow capturing and rendering with on-body sensor network.
Educational and Professional Qualifications
- 2007 - 2011 PhD. in Computer Science, the University of Nottingham, UK
- 2005 - 2007 MSc. in Information Technology for Manufacture, the University of Warwick, UK
- 2004 - 2005 TOEFL English Training Course, Shanghai Oriental School, China
- 2000 - 2004 BSc. in Computer Science, Harbin Engineering University, China
Multi-Target Detection and Tracking, Human Activity Analysis, Weakly Supervised Learning, Multiple-Kernel Learning, Structured Prediction, and Deep Learning.