Mufti Mahmud is a Senior Lecturer in Computing and Technology at the School of Science and Technology. Dr Mahmud has developed a research portfolio spanning robotics, AI and Machine Learning (including co-robotics), assistive robotics, companion robotics. His team’s approach is to address the health and care needs of an ageing population using assistive tools and technologies in the form of robots and automated systems. These capabilities will be essential for many future health applications such as telehealth and telenostics.

We combine computational intelligence and big data technologies to convert the ever-expanding amount of raw data to smart data and build predictive, secure and adaptive systems aiming personalized services towards improving quality of life.”

Dr Mufti Mahmud

Current Research Areas & Activities

Next generation secure healthcare and patient monitoring platform with advanced
data and signal analytics

Assisting the elderly in activities of daily living using companion robotics

Interfacing assistive robotics with neuro-physiological signals

Specialises in

High-Resolution Brain-Chip Interfacing

Neuro-prosthetics & Rehabilitation Engineering


Secure Cyber-Physical Systems and Internet of Things

Understanding Neural & Neuromuscular Behaviour through Modelling

Advanced Machine Learning for Biological Data Analysis

Advanced Machine Learning for Crowd Analysis

Selected Publications

M. Asif-Ur-Rahman, F. Afsana, M Mahmud, M.S. Kaiser, et al. (2019). Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things. IEEE Internet of Things Journal 6, 4049–4062.

S. W. Yahaya, A. Lotfi, M. Mahmud. (2019). A Consensus Novelty Detection Ensemble Approach for Anomaly Detection in Activities of Daily Living, Applied Soft Computing, 83(2019), 105613, doi: 10.1016/j.asoc.2019.105613.

S.W. Yahaya, A. Lotfi, M. Mahmud. (2019). A similarity measure approach for identifying causes of anomaly in activities of daily living. In: Proc. 12th ACM Intl. Conf. PErvasive Technologies Related to Assistive Environments, pp. 575-579. ACM.

M. Mahmud, M.S. Kaiser, M.M. Rahman, M.A. Rahman, A. Shabut, et a. (2018). A brain-inspired trust management model to assure security in a cloud based IoT framework for neuroscience ap