​​AI-Driven Approaches to Enhance Human Activity Recognition​

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

Cruciani, F., Nugent, C.D., Quero, J.M., Cleland, I., McCullagh, P., Synnes, K., Hallberg, J., Personalizing activity recognition with a clustering based semi-population approach, 2020, IEEE Access, 8, 9258905, , 10.1109/ACCESS.2020.3038084.

Razzaq, M.A., Cleland, I., Nugent, C., Lee, S., Semimput: Bridging semantic imputation with deep learning for complex human activity recognition, 2020, Sensors (Switzerland), 20, 10, 2771, 10.3390/s20102771.

Ni, Qin, Timothy Patterson, Ian Cleland, and Chris Nugent. "Dynamic detection of window starting positions and its implementation within an activity recognition framework." Journal of biomedical informatics 62 (2016): 171-180.

Cruciani, F., Vafeiadis, A., Nugent, C., Cleland, I., McCullagh, P., Votis, K., ... & Hamzaoui, R. (2020). Feature learning for human activity recognition using convolutional neural networks. CCF Transactions on Pervasive Computing and Interaction, 2(1), 18-32.

Ni, Q., Cleland, I., Nugent, C., García Hernando, A.B., de la Cruz, I.P., Design and assessment of the data analysis process for a wrist-worn smart object to detect atomic activities in the smart home, 2019, Pervasive and Mobile Computing, 56, 1, , 10.1016/j.pmcj.2019.03.006.

Patterson, T., Khan, N., McClean, S., Nugent, C., Zhang, S., Cleland, I., Ni, Q., Sensor-Based Change Detection for Timely Solicitation of User Engagement, 2017, IEEE Transactions on Mobile Computing, 16, 10, 7784795, 10.1109/TMC.2016.2640959.

Cleland, I., Kikhia, B., Nugent, C., Boytsov, A., Hallberg, J., Synnes, K., McClean, S., Finlay, D., Optimal placement of accelerometers for the detection of everyday activities., 2013, Sensors (Basel, Switzerland), 13, 7, , 10.3390/s130709183.