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Salisu Yahaya

Salisu Yahaya

Lecturer

Computer Science

Staff Group(s)
Computing and Technology

Role

Salisu Wada Yahaya is a Lecturer with the Department of Computer Science at Nottingham Trent University, where he is also a member of the Computational Intelligence and Applications (CIA) research group.

Career overview

Salisu Wada Yahaya received a B.Sc. degree in Computer Science from Nasarawa State University Keffi. He also received an MSc. in Cybernetics and Communication from Nottingham Trent University (NTU), where he is currently studying for a PhD in Computer Science. Before his current role, Salisu worked as a system administrator, a sessional tutor at Nottingham Trent International College and a part-time lecturer at Nottingham Trent University.

Research areas

Salisu's research interest is in the application of computational intelligence for human activity recognition, behaviour modelling and abnormality detection.

External activity

Member of the IEEE Computational Intelligence Society (2019 - Present)

Publications

Journals:

  1. Yahaya S.W., Lotfi A., Mahmud M., Towards a Data-Driven Adaptive Anomaly Detection System for Human Activity. Pattern Recognition Letters. 2021;
  2. Yahaya S.W., Lotfi A., Mahmud, M., Detecting Anomaly and Its Sources in Activities of Daily Living. SN Computer Science. 2021;2:14.
  3. Yahaya S.W., Lotfi A., Mahmud M., A consensus novelty detection ensemble approach for anomaly detection in activities of daily living. Applied Soft Computing. 2019; 83:105613.
  4. Lotfi A., Langensiepen C., Yahaya S.W., Socially Assistive Robotics: Robot Exercise Trainer for Older Adults. Technologies. 2018; 6(1):32.

Conferences:

  1. Yahaya S.W., Lotfi A., Mahmud M., Towards the Development of an Adaptive System for Detecting Anomaly in Human Activities, 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia, 2020, pp. 534-541.
  2. Yahaya S.W., Lotfi A., Mahmud M., Machado P., Kubota N., Gesture Recognition Intermediary Robot for Abnormality Detection in Human Activities, 2019 IEEE Symposium Series on Computational Intelligence (SSCI), Xiamen, China, 2019, pp. 1415-1421.
  3. Yahaya S.W., Lotfi A., Mahmud M., A similarity measure approach for identifying causes of anomaly in activities of daily living. In: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '19), Greece, 2019.
  4. Yahaya, S. W., Lotfi, A., Mahmud, M., A Framework for Anomaly Detection in Activities of Daily Living using an Assistive Robot. UK-RAS19 Conference: “Embedded Intelligence: Enabling & Supporting RAS Technologies” Proceedings, 2019, pp 131-134.
  5. Yahaya S.W., Langensiepen C., Lotfi A. (2019) Anomaly Detection in Activities of Daily Living Using One-Class Support Vector Machine. In: Advances in Computational Intelligence Systems. UKCI 2018. Advances in Intelligent Systems and Computing, 2018, 840
  6. Lotfi A., Langensiepen C., Yahaya S.W., Active and Healthy Ageing: Development of a Robotic Platform as an Exercise Trainer. In: Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '17). Greece, 2017.