Dr Sandra Fernando is an Associate Professor and leads the Assistive Technology Research Group at the School of Computing and Digital Media.
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Sandra Fernando
Sandra is is an Associate Professor at the School of Computing and Digital Media and holds a PhD in Computer Science. She is a senior fellow of HEA, holds a PG qualification in Vocational Subject Specialist Mentoring and contributes as a mentor. She has over 20 years of experience in the academic sector and worked in the software industry in the areas of engineering and quality assurance.
Sandra's academic knowledge and teaching experience were gained at Goldsmiths, University of London, University of Greenwich, Lewisham College and Southwark College. She has prior experience in designing and leading Foundation Degree programmes and partnership linking work. She currently manages many international academic partnerships in the school.
She has won internal bids for data science research, external bids for assistive technology research and leads the Assistive Technology research group in the school. She has broad experience in working with blind and visually impaired people, innovated a computer-aided drawing technology for blind people.
The quality of her research outputs has been recognised as internationally excellent and contributed to the school's submission in REF 2021. She is a member of the Empowering London Research Centre and engaged in the 'Giving back to the city' initiatives. She is the school's KTP Champion, and ECR lead for the university policy group.
She supervises many PhD students and is actively looking to recruit more researchers.
- Data and Web Development
- Big Data and Visualization
- Programming
Sandra's responsibilities encompass leading the Data Science BSc course, managing partner institute courses, and overseeing modules. She delivers lectures and tutorials, invigilates exams, provides assessments and feedback, and offers student guidance and support. Additionally, she supervises projects, actively participates in subject area development, leads both external and internal research projects, and engages in outreach activities.
Sandra's current research is focused on development of technologies to assist people with disabilities. Having previously taught blind students and developed assistive learning technologies, she now focuses on formally modelling the creative processes behind assistive technology development. Sandra Fernando’s research was supported by a grant from the MACS (Microphthalmia, Anophthalmia and Coloboma Support) national charity, UK and linked with other charities such as Inner Vision, VisionBridge, Show Me.
Her research interests include:
- Assistive technologies - current projects
- Big data AI and data analytics
- Learning technologies
- Alibakhshikenari, M., Fernando S., etc. (2023), “Breast Cancer Detection Based on Simplified Deep Learning Technique with Histopathological Image Using BreaKHis Database,”, Radio Science Journal, 21 Nov. 2023, pp.1-18.DOI: 10.1029/2023RS007761.
- Lewis J, S Fernando. (2023) Haringey Employment Gap Research Report (2023), Haringey Employment Gap Research 2023London Metropolitan University, London.
- Lewis, Jane, Fernando, Sandra, Nyby, Josefine, Yu, Qicheng, Gay, Dionne and Flynn, Jimmy (2023) Islington disability and long-term health conditions employment project: final report.London Metropolitan University, London.
- Fernando S., Ndukwe C, (2023), “Image Recognition Tools for Blind and Visually Impaired Users,” ACM Transactions on Accessible Computing. In review.
- Maharajan S, Shrestha S, Fernando S,(2023) Sign Language Detection and Translation using Smart Glove', International conference on Innovative Computing and communication (ICICC) https://icicc-conf.com/, India (in press)
- Dharmarathne G, Ouazzane K, , Shrestha S, Fernando S, (2024) Exploring Machine Learning Models for Age Recognition, , International conference on Innovative Computing and communication (ICICC) https://icicc-conf.com/, India (in press)
- Adekoya-Col. T , Fernando S, (2023) From Text To Insights: Building A Dynamic Dashboard For Sentiment Analysis - A Twitter Case Study, International Journal of Data Science and Analytics(in review)
- Karia V, Fernando S, ABDELWAHED, Abdallah (2023) Analytical Study of disabled immigrants and their employment, International Journal of Data Science and Analytics(in review)
- Nyby Josefine, Lewis Jane, Fernando Sandra (2023) Understanding the barriers and the possibilities - a study of people with disabilities and their perception of the labour market, Warsaw, Poland, Stream 10. Health in the world of work - Session 2 https://espanet-warsaw2023.org/wp-content/uploads/Programme-12.pdf
- Shrestha S., Fernando S., Patel P., Pun M., (2023), “Employability of University Leavers Using a Descriptive Analytics Case Study,” International Journal of Learning and Teaching (IJLT), 9(3): 175-185, DOI: 10.18178/ijlt.9.3.175-185.
- Fernando S., Sowinski-Mydlarz, Katanani A., (2023), “Cloud Spark Cluster to analyse English Prescription Big Data for NHS Intelligence,” Springer (ICDAM), London. DOI: 10.1007/978-981-99-6544-1.
- Alibakhshikenari, M., Fernando S., etc. (2023), “Breast Cancer Detection Based on Simplified Deep Learning Technique with Histopathological Image Using BreaKHis Database,”, Radio Science Journal, 21 Nov. 2023, pp.1-18. DOI: 10.1029/2023RS007761.
- Fernando S., Virdee B., Ouazzane K., (2022), “A Hybrid Approach to Computer Aided Drawing Tool for Blind People,” Journalof Software: Evolution and Process. 17 May, 2023, pp.1-33. DOI: 10.22541/au.168431875.54049181/v1
- Fernando S., Ohene-Djan J. (2021), “A Computer Aided Drawing System Evaluation with Early and Late Blind Users,” Assistive Technology (The Official Journal of RESNA). DOI: 10.1080/10400435.2020.1829745
- Fernando S., and Ohene-Djan, J. (2020), “An Empirical Evaluation of a Graphics Creation Technique for Blind and Visually Impaired Individuals,” British Journal of Visual Impairment, DOI: 10.1177/0264618620911422
- Ohene-Djan, J. and Fernando, S. (2018), "Screen Navigation System for Visually Impaired People", Journal of Enabling Technologies, vol.12(3): 114-128. https://doi.org/10.1108/JET-04-2018-0018.
- Ohene-Djan and S. Fernando (2016), “Drawing for Blind Learners: Assistive Technology for Graphical Design,” IEEE 16th International Conference on Advanced Learning Technologies (ICALT), Austin, TX:436-440. DOI: 10.1109/ICALT.
- Sandra Fernando, (2015), “Blind Drawing: Investigation into Screen Location Tracking for Computer Aided Interactive Drawing,” SIGACCESS Access. Comput. Vol.111, pp. 6-9. https://doi.org/10.1145/2809904.2809906
External funding from Microphthalmia, Anophthalmia and Coloboma Support (MACS) charity for blind drawing research work.
Several internal Fundings:
- A research to develop an analytical learning model using big data for graduate outcome data projection on multiple themes and comprehensive solution generation
- Cloud Spark Cluster to analyse English Prescription Big Data for NHS Intelligence
- Patterns of Vitamin D prescriptions in the UK
Academic liaison tutor for international academic partners: NEXT Sri Lanka, ESOFT Sri Lanka.
External examiner: Greenwich University - computing, business computing, computing (network systems), computing (information systems), computing (ext) and computing (ext ugic).
Consultancy work - Islington Council, Haringey Council
Associate Editor - Assistive Technology, the official journal of RESNA
Reviewer - Computational Intelligence, Wiley
Member IEEE
Member of the British Computer Society
SFHEA: Senior Fellow of Advance-HE
Speaker at International Conference
Dr Sandra Fernando, BSc (Hons), MSc, PhD, SFHEA, MBCS.
Head of Assistive Technology Research Group,
Associate Professor, Course Leader, Data Science Consultant.
School of Computing and Digital Media, London Metropolitan University.