Yiannis Demiris is a Professor in Human-Centred Robotics at Imperial, where he established the Personal Robotics Laboratory. He holds a PhD in Intelligent Robotics, and a BSc(Hons) in Artificial Intelligence and Computer Science, both from the University of Edinburgh. He has been a European Science Foundation (ESF) junior scientist Fellow, and a COE Fellow at the Agency of Industrial Science and Technology (AIST - ETL) of Japan. He is currently a Fellow of the Institute of Engineering and Technology (FIET), Fellow of the British Computer Society (FBCS) and Fellow of the Royal Statistical Society (FRSS).
Prof. Demiris' research interests include active perception, machine learning, user modelling, and cognitive control architectures in order to determine how intelligent robots can generate personalised assistance to humans in order to improve their physical, cognitive and social well being. He participates in multiple EU research projects, including FP7 STREP WYSIWYD (What You Say in What You Did) where his group will work on active learning for humanoid assistive robots, and (starting in March 2015) the H2020 project PAL (Personal Assistant for Healthy Lifestyle, 2015-2019), where his group will be using machine learning to model diabetic users to optimise the medical assistance that robots and avatars on mobile devices can provide to their users.
His teaching includes (a) human-centered robotics, a 4th year research-led module on how to design and build a robot, and evaluate it with real users, and (b) Mobile Healthcare and Machine Learning, a 4th year research-led module on how to design and implement mobile healthcare systems that personalise their behaviour using data about their users. He received the 2012 Rector's Award for Teaching Excellence, and the 2012 FoE award for excellence in Engineering Education.
For up-to-date information, readers are advised to look at the Personal Robotics laboratory webpage at http://www.imperial.ac.uk/PersonalRobotics where information is more frequently updated.
et al., 2012, A Quantum-Statistical Approach Toward Robot Learning by Demonstration, Ieee Transactions on Robotics, Vol:28, ISSN:1941-0468, Pages:1371-1381-1371-1381
et al., 2013, A syntactic approach to robot imitation learning using probabilistic activity grammars, Robotics and Autonomous Systems, Vol:61, ISSN:0921-8890, Pages:1323-1334
et al., 2014, Information Processing in the Mirror Neuron System in Primates and Machines, Neuroinformatics, Vol:12, ISSN:1539-2791, Pages:63-91
et al., 2011, Echo State Gaussian Process, IEEE Transactions on Neural Networks, Vol:22, ISSN:1045-9227, Pages:1435-1445
et al., 2012, Collaborative Control of a Robotic Wheelchair: Evaluation of Performance, Attention and Workload, IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, Vol:42, ISSN:1083-4419, Pages:876-888