Dr Hamed Hamzeh

Dr Hamed Hamzeh

I'm a Postdoctoral research associate at the Centre for Parallel and Distributed Computing (CPC) at the University of Westminster. I received my Ph.D. in cloud computing from Bournemouth University in 2021 and hold an MSc degree in data science from Istanbul Sehir University, Turkey. I joined the CPC in 2021 and am working on various projects (Currently conducting research and developing components related to the projects) such as MiCADO (which is an auto-scaling framework for Docker containers, orchestrated by Kubernetes), ASCLEPIOS (which offers the ability to users to verify the integrity of their medical devices before receiving them while receiving simultaneously certain guarantees about the trustworthiness of their cloud service provider.), DigitBrain ( is an EU innovation program to give SMEs easy access to digital twins), and COVERSATILE (aims at increasing the adaptation capacity, resilience, and flexibility of the European manufacturing sector to satisfy a sudden rise in demand for vital medical supplies.

My areas of research are cloud computing, computer networks, data science, and algorithms. My Ph.D. thesis is titled "Fairness for resource allocation in cloud computing". Accordingly, I proposed novel algorithms to tackle unfair resource allocation and task scheduling in heterogeneous cloud settings. I published several papers at international conferences/journals and participated as a technical committee member in the IEEE ICCCS conference for two consecutive years.


  • H. Hamzeh, S. Meacham, K. Khan, K. Phalp and A. Stefanidis, "MRFS: A Multi-resource Fair Scheduling Algorithm in Heterogeneous Cloud Computing," 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC), 2020, pp. 1653-1660, doi: 10.1109/COMPSAC48688.2020.00-18.
  • H. Hamzeh, S. Meacham and K. Khan, "A New Approach to Calculate Resource Limits with Fairness in Kubernetes," 2019 First International Conference on Digital Data Processing (DDP), 2019, pp. 51-58, doi: 10.1109/DDP.2019.00020.
  • H. Hamzeh, S. Meacham, B. Virginas, K. Khan and K. Phalp, "MLF-DRS: A Multi-level Fair Resource Allocation Algorithm in Heterogeneous Cloud Computing Systems," 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS), 2019, pp. 316-321, doi: 10.1109/CCOMS.2019.8821774.
  • H. Hamzeh, S. Meacham, K. Khan, K. Phalp and A. Stefanidis, "FFMRA: A Fully Fair Multi-Resource Allocation Algorithm in Cloud Environments," 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation, 2019, pp. 279-286, doi: 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00091.
  • H. Hamzeh, M. Hemmati and S. Shirmohammadi, "Priced-Based Fair Bandwidth Allocation for Networked Multimedia," 2017 IEEE International Symposium on Multimedia (ISM), 2017, pp. 19-24, doi: 10.1109/ISM.2017.14.
  • Hamzeh, Hamed Meacham, Sofia Botond, Virginas Phalp, Keith. (2018). Taxonomy of Autonomic Cloud Computing. International Journal of Computer and Communication Engineering. 7.
  • Georgia, Isaac Meacham, Sofia Hamzeh, Hamed Stefanidis, Angelos Phalp, Keith. (2018). An Adaptive E-Commerce Application using Web Framework Technology and Machine Learning.
  • Hamzeh, Hamed Hemmati, Mahdi Shirmohammadi, Shervin. (2017). Bandwidth Allocation with Fairness in Multipath Networks. International Journal of Computer and Communication Engineering. 6. 151-160.
  • H. Hamzeh, S. Meacham, K. Khan, A. Stefanidis and K. Phalp, "H-FFMRA: A Multi Resource Fully Fair Resources Allocation Algorithm in Heterogeneous Cloud Computing," 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 2021.

  • Centre for Parallel Computing

In brief

Research areas

Cloud Computing, Software Engineering, Data Science and Algorithms

Skills / expertise

AWS, Kubernetes, Python, Java, Data Analysis and Ubuntu

Supervision interests

Cloud Computing , Algorithms, Data Science, Software Engineering and Computer networks