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Department of Computer Science and Technology

  • PhD Student

I am a first year PhD student in the Systems Research Group (SRG) at the Department of Computer Science and Technology (also known as “The Computer Lab”), working under the supervision of Professor Richard Mortier. I am a member of Clare College.

In 2018, I was awarded the Said Foundation Cambridge Scholarship , to study the MPhil in Advanced Computer Science (ACS) at the Computer Lab. Before moving to Cambridge, I co-founded several projects for empowering engineering students in Syria, including the award-winning education enterprise: Wikilogia.

I am interested in the convergence of the IT and teclcom worlds, as well as the the role of the cloud-native and open source movements in shaping the future of cloud and network infrastructure. I have deep passion for social entrepreneurship and the role of digital infrastructure in addressing development and sustainablity challenges across the globe.


The focus of my research is on building self-scaling network services on top of next generation infrastructure (IoT/5G/edge), leveraging lightweight virtualization techniques and distributed tracing. My work falls under the Compute First Networking research project.

Research interests

  • Cloud and Edge Computing
  • Microservices and Serverless
  • Operating Systems and Middleware
  • Networked and Distributed Systems
  • Machine Learning Systems


  • Operating Systems (LT 2021)


Conference proceedings

  • Isstaif, AAT. and Mortier, R., 2023. Towards Latency-Aware Linux Scheduling for Serverless Workloads Proceedings of the 1st Workshop on SErverless Systems, Applications and MEthodologies,
    Doi: 10.1145/3592533.3592807
  • Isstaif, AAT., 2020. Self-managed services using MirageOS unikernels Middleware 2020 Doctoral Symposium - Proceedings of the 2020 21st International Middleware Conference Doctoral Symposium, Part of Middleware 2020,
    Doi: 10.1145/3429351.3431748
  • Isstaif, AAT. and Alhafez, N., 2018. Performance Model of Apache Cassandra Under Heterogeneous Workload Using the Quantitative Verification Approach Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 11178 LNCS
    Doi: 10.1007/978-3-030-02227-3_7
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