Cloud · Edge · IoT · Intelligent Systems
Syed Mafooq
Ul Hassan
PhD Candidate & Research Associate at the Data Intensive Computing Laboratory
I develop intelligent and reproducible resource-management methods for the cloud-edge-IoT continuum, with a focus on Kubernetes simulation, multi-agent reinforcement learning, and scheduling for hyper-distributed systems.
Based in Limassol, Cyprus
Research focus
Cognitive resource management across heterogeneous infrastructures
About
Engineering intelligent infrastructure for the computing continuum.
I am a PhD candidate and Research Associate at the Cyprus University of Technology, working within the Data Intensive Computing Laboratory (DICL). My doctoral research investigates cognitive resource management in cloud, edge, and IoT environments.
At DICL, I contribute to the EU-funded HYPER-AI project and lead the development of a Kubernetes-based workload simulator used to evaluate rule-based and learning-based scheduling strategies under reproducible conditions.
My background combines computer science, electrical engineering, critical-infrastructure systems, simulation, machine learning, optimisation, and hands-on software development.
View my DICL profile ↗Research interests
From autonomous scheduling to resilient infrastructure.
My work sits at the intersection of distributed systems, artificial intelligence, and critical infrastructure.
Cloud-Edge-IoT Continuum
Architectures and orchestration methods for heterogeneous, geographically distributed computing resources.
Multi-Agent Reinforcement Learning
Cooperative and decentralised learning methods for dynamic task allocation and scheduling.
Kubernetes Simulation
High-fidelity, configurable environments for repeatable evaluation of scheduling policies.
Resource Optimisation
Cost, energy, latency, bandwidth, and utilisation-aware decision making across the continuum.
Critical Infrastructure
Data-driven modelling, monitoring, and simulation for water, energy, and transportation systems.
Machine Learning Systems
Practical ML pipelines, experimentation, reproducibility, and intelligent automation.
Selected publications
Recent research contributions.
2026
DARO: An Auction-Based Multi-Agent Reinforcement Learning Framework for Task Scheduling in the Cloud Continuum
Syed Mafooq Ul Hassan, Marios Touloupou, Jacopo Castellini, Pablo Strasser, Alexandros Kalousis, and Herodotos Herodotou.
View publication ↗2026
A Modular Kubernetes Workload Simulator for Evaluating Learning-Based Scheduling Policies
Marios Touloupou, Syed Mafooq Ul Hassan, Jacopo Castellini, Pablo Strasser, Alexandros Kalousis, and Herodotos Herodotou.
View publication ↗2026
Hypertool: A Resource Abstraction and Lifecycle Management Framework for Heterogeneous Cloud Environments
Michalis Loukeris, Nektarios Deligiannakis, Vassilis Papataxiarhis, Panagiotis Kechriniotis, Syed Mafooq Ul Hassan, Nicolas Louca, Herodotos Herodotou, and Stathes Hadjiefthymiades.
View publication ↗2026
DACCA: Distributed Adaptive Cloud Continuum Architecture
Nektarios Deligiannakis, Vassilis Papataxiarhis, Michalis Loukeris, Stathes Hadjiefthymiades, Marios Touloupou, Syed Mafooq Ul Hassan, et al.
View publication ↗Selected projects
Research translated into working systems.
Open-source research software
2024–Present
Kubernetes Workload Simulator
A modular simulator for evaluating scheduling strategies across the cloud-edge-IoT continuum, including configurable clusters, synthetic workloads, detailed traces, and integration with QMIX-based multi-agent reinforcement learning.
KubernetesPythonQMIXSimulationMARL
Explore repository ↗
QGIS plugin
QSU2
Developed a QGIS plugin for generating SU2 simulation files within the EU-funded PathoCERT project.
QGISPythonCFD
Water systems
Hydraulic & Water-Quality Toolkit
Modelled pressure, inflow, chlorine dynamics, contamination detection, and sensor-placement scenarios using EPANET.
EPANETOptimisationSimulation
Smart grids
Grid Automation using IoT
Implemented substation automation and monitoring to improve visibility and operational efficiency.
IoTPower systemsEmbedded systems
Transportation
San Francisco MFD via SUMO
Derived macroscopic fundamental diagrams from peak-hour traffic simulations and analysed network flow-density relationships.
SUMOMobilityData analysis
Experience
Research, engineering, and teaching.
Aug 2024–Present
Research Associate
Data Intensive Computing Laboratory, Cyprus University of Technology
Research on intelligent resource management in the IoT-edge-cloud continuum and development of Kubernetes-based simulation and MARL scheduling systems.
Sep–Dec 2025
Teaching Assistant — Blended Intensive Program
European University of Technology · Hybrid
Supported international IoT labs and application-pipeline exercises using Node-RED, data visualisation, and hands-on technical mentoring.
Jun 2023–May 2024
Teaching Assistant
University of Cyprus
Delivered tutorials, grading, and instructional support for Electronic Devices and Circuits.
Jan 2022–Jun 2024
Research Engineer I
KIOS Center of Excellence
Contributed to PathoCERT and Oceanos, developed geospatial tools, performed water-system CFD simulations, and studied critical-infrastructure interdependencies.
Aug 2018–Dec 2020
Teaching Assistant
FAST National University
Supported programming, microprocessor interfacing, electronics, and applied-calculus courses through labs and one-to-one mentoring.
Education
Interdisciplinary foundations.
PhD in Computer Science
Cyprus University of Technology · DICL
Research: Intelligent resource management in the IoT-edge-cloud continuum.MSc in Intelligent Critical Infrastructure Systems
University of Cyprus
Thesis on synthetic image generation using GANs for emergency-response deep learning.BSc in Electrical Engineering
FAST National University, Pakistan
Graduated with a 3.77/4.00 GPA and a full academic scholarship.Blended Intensive Program in Internet of Things
Technological University Dublin
IoT communication protocols, data management, and application development.Technical toolkit
Tools for research and implementation.
Programming
PythonC++MATLABSimulinkBash
Platforms
KubernetesDockerLinuxGit
Data & AI
PandasNumPyJupyterMachine LearningOptimisationMARL
Engineering tools
QGISEPANETSUMOPSCADProteusArduino
Contact
Let’s discuss research, collaboration, or open-source systems.
I am open to academic collaboration and conversations around cloud-continuum orchestration, Kubernetes simulation, and intelligent scheduling.