Dr Shirin Enshaeifar
Academic and research departmentsCentre for Vision, Speech and Signal Processing (CVSSP), Department of Electrical and Electronic Engineering.
I am a Senior Research Fellow in Machine Learning and Healthcare Informatics and the Deputy Technical Lead of TIHM for Dementia project at the Department of Electronic Engineering, University of Surrey. I am also a Fellow of the UK Higher Education Academy. I completed my PhD degree in biomedical signal processing and my MSc studies in medical imaging at the University of Surrey, in 2016 and 2013, respectively. I received my BSc degree in biomedical engineering from the University of Isfahan in 2010.
I was awarded the Industrial Advisory Board Award for Excellence in Research at the Department of Electronic and Electronic Engineering, in 2018.
Areas of specialism
Machine learning and data analytics with application in healthcare and smart cities;
Analytical modelling, simulations, and statistical analysis
University roles and responsibilities
- Senior Research Fellow in Healthcare Informatics
- Deputy Technical Lead for TIHM for Dementia Project with focus on dementia care, funded by the Department of Health, http://www.sabp.nhs.uk/tihm
- Quality Control Manager for EU-H2020 IoTCrawler Project with focus on developing a search engine for Internet of Things devices, funded by the European Commission
- The Industrial Advisory Board Award for Excellence in Research, Department of Electronic and Electronic Engineering, 2018
- The Best Research Potential, Department of Computer Science, 2014
- HSJ Award 2018 for ‘Improving Care with Technology’ (TIHM for Dementia project)
- Guildford Innovation Award 2018 for ‘Most Outstanding Innovation Project’ (TIHM for Dementia project)
- Regional winner in the NHS 70 Parliamentary Awards 2018 for ‘NHS Future’ (TIHM for Dementia project)
- Best Mental Health Initiative of 2017 at the EHI Awards (TIHM for Dementia project)
- Highly Commended in the HSJ Value Award 2017 for ‘IT in Clinical Services (TIHM for Dementia project)
Keynote and invited talks
- AI and Data Analytics for Healthcare, Creative/Smart Healthcare Workshop, London, UK
- The Internet of Things for Dementia Care, IoT Week 2017, Geneva, Switzerland
- Data Analytics for Dementia Care, Technology and Dementia Conference, London, UK
- The Internet of Things in Healthcare, IEEE International Conference on Internet of Things Applications and Infrastructure, Isfahan, Iran
- Technology and Dementia, Pint of Science Festival, Guildford, UK
- The Internet of Things and its Applications, The IoT Meetup, Brighton, UK
My research focuses on the development of machine learning and data analytics algorithms for information processing in real-world applications. My research goal is to develop intelligent data discovery, analytics and representation methods in order to integrate heterogeneous sensory data and extract actionable insights from raw data, with application in healthcare and smart cities.
- Laboratories, Design and Professional Studies Module
- Internet of Things Module (guest lecture)
Postgraduate research supervision
- Mr Honglin Li: Deep Learning for Dynamic Data Streams
- Ms Roonak Rezvani: Probabilistic Models for Time-series Data Analysis
- Ms Narges Pourshahrokhi: Machine Learning for Analysing Dynamic Data Streams
- S. Enshaeifar, P. Barnaghi, et al., “Internet of Things for Dementia Care”, (in Press) IEEE Internet Computing Magazine, 2017.
- S. Enshaeifar, N. Farajidavar, et al., “Recognising Bone Loading Exercises In Older Adults Using Machine Learning” (Abstract), Medicine& Science in Sports & Exercise, 49(5S):650, 2017.
- S. Enshaeifar, C.C. Took, C. Park and D. P. Mandic, “Quaternion Common Spatial Patterns”, (in Press) IEEE Transaction on Neural Systems and Rehabilitation Engineering, DOI: 10.1109/TNSRE.2016.2625039, 2016.
- S. Enshaeifar, S. Kouchaki, C.C. Took and S. Sanei, “Quaternion Singular Spectrum Analysis of Electroencephalogram with Application in Sleep Analysis”, IEEE Transaction on Neural Systems and Rehabilitation Engineering, vol. 24, no. 1, pp. 57-67, 2016.
- S. Enshaeifar, L. Spyrou, S. Sanei and C.C. Took, “A Regularised EEG Informed Kalman Filtering Algorithm”, Elsevier Biomedical Signal Processing and Control, vol. 25, pp. 196-200, 2016.
- S. Enshaeifar, S. A. Hoseinitabatabaei, A. Ahrabian and P. Barnaghi, “Pattern Identification for State Prediction in Dynamic Data Streams”, in Proc. of IEEE International Conference on Internet of Things (iThings), 2017.
- A. Ahrabian, S. Enshaeifar, C. C. Took and P. Barnaghi, “Stream Data Analysis As a Web Service: A Case Study Using IoT Sensor Data”, in Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
- Y. Fathy, P. Barnaghi, S. Enshaeifar and R. Tafazolli, “A Distributed In-network Indexing Mechanism for the Internet of Things”, in Proc. of IEEE World Forum on Internet of Things (WF-IoF), 2016.
- S. Enshaeifar, C.C. Took, S. Sanei and D. P. Mandic, “Novel Quaternion Matrix Factorisation”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3946-3950, 2016.
- S. Mahvash, S. Enshaeifar, S. Sanei and M. Ghavami, “Classification of Awake, REM, and NREM from EEG via Singular Spectrum Analysis”, IEEE International Conference on Engineering in Medicine and Biology Society (EMBS), pp. 4769-4772, 2015.
- S. Kouchaki, S. Enshaeifar, C. C. Took and S. Sanei, “Complex Tensor based Blind Source Separation of EEG for Tracking P300 Subcomponents”, IEEE International Conference on Engineering in Medicine and Biology Society (EMBS), pp. 6999-7002, 2015.
- K. Eftaxas, S. Enshaeifar, O. Geman, S. Kouchaki and S. Sanei, “Detection of Parkinsons Tremor from the EMG Signals; A Singular Spectrum Analysis Approach”, IEEE International Conference on Digital Signal Processing (DSP), pp. 398-402, 2015.
- S. Enshaeifar, S. Sanei and C.C. Took, “Singular spectrum analysis for tracking of P300”, IEEE International Joint Conference on Neural Networks (IJCNN), pp. 502-506, 2014.
- S. Enshaeifar, S. Sanei and C.C. Took, “An eigen based approach for complex valued forecasting”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6014-6018, 2014.
- O. Diaz, P. Elangovan, S. Enshaeifar, M.C. Veale, M.D. Wilson, P. Seller, R. Cernik, S. Pani, K. Wells, “Breast CT image simulation framework for optimisation of lesion visualisation,” IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), pp. 1-5, 2013.