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Dr. Tahmina Zebin is a Senior Lecturer in Computer Science. Prior to this post, she was a Lecturer in the School of Computing Sciences at the University of East Anglia and has led an On-device and Explainable AI Research Group.  She completed her PhD studies in 2017 from the University of Manchester. Following her PhD, Tahmina was employed as a postdoctoral research associate on the EPSRC funded project Wearable Clinic: Self, Help and Care at the University of Manchester and was a Research Fellow in Health Innovation Ecosystem at the University of Westminster. Her research expertise includes Advanced Video and Signal Processing, Explainable and Inclusive AI, Human Activity Recognition, Risk Prediction Modelling from Longitudinal Electronic Health Records using various statistical, machine learning and deep learning techniques.


Tahmina pursued her PhD studies at the University of Manchester in Electrical and Electronic Engineering and she had been the recipient of the Presidents Doctoral Scholarship (2013-2016) for this. She received her first degree and an MS in Applied Physics, Electronics, and Communication Engineering from the University of Dhaka, Bangladesh. She also completed an M.Sc in Digital Image and Signal Processing from the University of Manchester in 2012. 

Newest selected publications

Zebin, T., Rezvy, S. and Luo, Y. (2022) 'An Explainable AI-Based Intrusion Detection System for DNS over HTTPS (DoH) Attacks'. IEEE Transactions on Information Forensics and Security, 17. pp. 2339 - 2349. ISSN: 1556-6013

Journal article

Zebin, T. and Rezvy, S. (2021) 'COVID-19 detection and disease progression visualization: Deep learning on chest X-rays for classification and coarse localization'. Applied Intelligence, 51 (2). pp. 1010 - 1021. ISSN: 0924-669X

Journal article

Rezvy, S., Zebin, T., Braden, B., Pang, W., Taylor, S. and Gao, XW. (2020) 'Transfer learning for endoscopy disease detection and segmentation with MASk-RCNN benchmark architecture'. CEUR Workshop Proceedings. pp. 68 - 72. ISSN: 1613-0073

Conference paper

Zebin, T., Rezvy, S. and Chaussalet, TJ. (2019) 'A deep learning approach for length of stay prediction in clinical settings from medical records'.2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE. pp. 59 - 63.

Conference paper

Zebin, T., Peek, N. and Casson, AJ. (2019) 'Physical activity based classification of serious mental illness group participants in the UK Biobank using ensemble dense neural networks'.2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). United States. 1 - 27 July. IEEE. pp. 1251 - 1254. ISSN: 1557-170X

Conference paper
More publications(16)