Najma Taimoor

Najma Taimoor BSc, MSc, Dipl.-Ing., PhD, FHEA

Lecturer in Computer Science (Secure Healthcare)

I am a Lecturer in Computer Science at the University of Greenwich, UK where I am part of the Centre for Sustainable Cyber Security. Prior to that, I was a research assistant in the School of Design at the University of Greenwich, where I was a key member of an EYES project funded by the EU. I am also a final year doctoral student in the Institute of Computer Technology at the Vienna University of Technology, Austria. Furthermore, I have earned a Masters in Healthcare and IT from the University of Applied Sciences, Austria with Distinction. My Master's thesis was funded by an Erasmus grant, which was developed under the supervision of Prof. Lilian H. Tang at the University of Surrey, UK. Moreover, I also have spent some time in leading software companies (e.g., Technocert, Austria) where I was involved in developing smart cyber-physical systems for critical infrastructures.

My current research is focused on developing safe and secure healthcare systems. I have published my research in esteemed journals and conferences, e.g., IEEE Access, and DSD. In addition to leading several technical modules at the University, I am also a Fellow of HEA, UK. I have taught culturally and technically diverse students at various Universities across the globe (including Pakistan, Qatar, and Austria).

Responsibilities within the university

  • Module leader for Operating System
  • Module leader for Principles of Software Engineering

Awards

Scholarship Grants

2018-1: TU Wien “Responsible and Ethical AI” (2022), DSD “Modelling of Multi-Level Personalised Health Condition” (2022) & TU Wien “Modelling Trust in AI” (2021).

Funded Projects

Reliable and Resilient Personalized Healthcare Services
Duration: 2020-2023
Role : Doctoral Student

The project aims to develop reliable and resilient IoT-based personalized healthcare services.

Ex Machina: The Emergence of the Legal Tech Industry and Future of the Legal Profession
Funding: HEIF (Higher Education Innovation Fund) UK
Duration: 2021
Role: Research Assistant

The proposed project aims to provide a study on the emerging legal-tech industry, addressing the legal and technical aspects of innovative data-driven tools in the legal profession. The project is funded by HEIF UK and costs approximately £25K. For current activities of the project, please visit here.

Rigorous Diagnosis of Retinal Vessel Diseases
Funding: Erasmus Grant jointly with University of Surrey, UK
Duration: 2019
Role: Project Assistant

The goal of this project was to develop a classifier that can rigorously diagnose selected retina diseases based on medical reasoning and data driven image analysis. The classifier diagnosed a disease not only on the basis of image data but will also employ medical reasoning to certify the initially determined diagnosis by the classifier.

Recognition

Invited talks

TU Wien “Responsible and Ethical AI” (2022), DSD “Modelling of Multi-Level Personalised Health Condition” (2022) & TU Wien “Modelling Trust in AI” (2021).

Research / Scholarly interests

Research Topics

  • Reliable and resilient healthcare systems
  • Trust modelling in healthcare systems
  • Medical statistics

Recent publications

Article

Taimoor, Najma and , Rehman, Semeen (2021), Reliable and resilient AI and IoT-based personalised healthcare services: A survey. IEEE. In: , , , . IEEE, IEEE Access, 10 . pp. 535-563 2169-3536 (Online) (doi: https://doi.org/10.1109/ACCESS.2021.3137364).

Conference proceedings

Taimoor, Najma and , Rehman, Semeen (2023), On the Validation of Multi-Level Personalised Health Condition Model. IEEE. In: 2022 25th Euromicro Conference on Digital System Design (DSD), , , 2022 25th Euromicro Conference on Digital System Design (DSD). IEEE, . pp. 599-606 . ISBN: 9781665474054ISSN: 2639-3859 (Print), 2771-2508 (Online) (doi: https://doi.org/10.1109/DSD57027.2022.00086).

Taimoor, Najma and , Rehman, Semeen (2022), Towards Multi-Level Modelling and Monitoring of Real-time Personalised Health Conditions. IEEE. In: 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), , , 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, . pp. 1-8 . ISBN: 9781665499972 (doi: https://doi.org/10.1109/ETFA52439.2022.9921687).