Available for research collaboration

Zia Ur Rehman.

PhD Researcher in Computer Science at the University of Limerick, building privacy-preserving and interpretable machine learning frameworks — where federated architectures, evolutionary algorithms, and green AI meet.

Federated Learning Explainable AI Evolutionary Algorithms Green AI Ensemble Learning
Explore my work Get in touch
Portrait of Zia Ur Rehman
01 · Lero · BDS Group
Federated Learning· Generative Models· Explainable AI· Evolutionary Algorithms· Green AI· Ensemble Learning· Parallel Computing· Privacy-Preserving ML· Federated Learning· Generative Models· Explainable AI· Evolutionary Algorithms· Green AI· Ensemble Learning· Parallel Computing· Privacy-Preserving ML·
02

About.

I'm a PhD researcher at the University of Limerick (Lero, BDS Group), working under the supervision of Prof. Conor Ryan.

My research sits at the intersection of privacy-preserving machine learning and interpretability. I'm developing frameworks that integrate ensemble methods through Grammatical Evolution into federated architectures — aligned with responsible AI and computational efficiency in distributed environments.

Before Limerick, I completed my MS in Computer Science at the Institute of Space Technology with Summa Cum Laude honors and Rank 1 (CGPA 4.0/4.0), and earned a Gold Medal for my BSc in Computer Engineering at UET Taxila.

03

Research focus.

i.

Federated Learning

Designing privacy-preserving training pipelines that scale across distributed clients without sacrificing model utility.

ii.

Evolutionary Algorithms

Using Grammatical Evolution to construct interpretable ensemble models that adapt to heterogeneous data environments.

iii.

Explainable AI

Building transparent learning systems where decisions can be traced, audited, and trusted — especially in healthcare contexts.

iv.

Green AI

Quantifying the energy footprint of ML workloads and engineering computationally efficient alternatives for sustainable AI.

v.

Parallel Computing

MPI-driven parallelization strategies to accelerate CNN training and federated workflows across multi-node clusters.

vi.

Generative Models

Exploring generative architectures for data augmentation in low-resource and privacy-sensitive learning regimes.

04

Selected publications.

Full publication list on Google Scholar ↗
05

Experience.

2025 — Present

Teaching Assistant — University of Limerick

Assisting in undergraduate and graduate computer science courses at UL. Academia

2019 — 2025

Lab Engineer — Institute of Space Technology, Islamabad

Conducted labs in Computer Vision, Machine Learning, Information Security, Digital Image Processing, Embedded Systems, and more. Supervised AI/CV projects and implemented MPI-based parallelization for ML optimization. Academia

2023

Computer Vision Consultant — Vision Insighta, Rawalpindi

Built OpenCV + Raspberry Pi interactive display systems, gesture-based presentation control, and virtual whiteboard solutions. Industry

2018

Embedded System Design Engineer — Barqi Labs, Rawalpindi

Automated scoreboards using PIC microcontrollers and IR sensors. Designed DTMF-controlled robotic cars, Bluetooth locks, and data loggers. Industry

2016

Engineering Intern — KSOFT, Islamabad

Worked on hardware interfacing for pathology lab and medical diagnostic equipment. Industry

06

R&D contributions.

Python · PyPI↗

EnergyEfficientAI

A Python library for real-time CPU, memory, and power monitoring during model training — built to analyze the energy footprint of ML workloads.

PyPI library
Python · MPI↗

MPI Parallel Programming

Materials and example code for parallel programming with MPI4Py, applied to machine learning workloads.

GitHub repository
Python · Security↗

Secure Software Development in Python

A practical workshop covering common Python security vulnerabilities and how to prevent them through hands-on coding exercises and secure development practices.

Workshop · GitHub Pages
Python · Workshop↗

AI Workshop

Comprehensive AI workshop materials covering practical machine learning, computer vision, and deep learning in Python.

GitHub repository
Python · Raspberry Pi↗

Raspberry Pi 5 Power Monitor

Real-time system monitoring dashboard built with Python and ttkbootstrap — CPU, RAM, temperature, clock frequency, and power.

GitHub repository
Python · Benchmarking↗

Languages × Energy

Comparison of programming languages with respect to energy consumption — a benchmarking study.

GitHub repository
Python · DEAP↗

Learn Evolutionary Algorithms

Hands-on implementations and tutorials for evolutionary computation, genetic algorithms, and grammatical evolution.

GitHub repository
07

Tools of the trade.

Languages

  • Python
  • C / C++
  • Embedded C
  • MATLAB
  • Verilog HDL
  • LaTeX

ML Frameworks

  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Keras
  • OpenCV
  • YOLOv5
  • MPI4Py
  • DEAP
  • Mediapipe

Hardware

  • Raspberry Pi
  • Arduino
  • PIC
  • FPGA (Artix-7)
  • PCB Design
  • Proteus
  • Vivado
  • MPLAB

Tooling

  • VS Code
  • PyCharm
  • Docker
  • GitHub
  • Jupyter
  • Anaconda
  • Overleaf
  • Linux (Ubuntu)
08

Let's connect.

Open to collaborations,
research conversations,
and academic opportunities.

If your work touches federated learning, evolutionary methods, explainable AI, or sustainable computing — I'd love to hear from you.

Email engrziaurrehman.kicsit@gmail.com ↗ LinkedIn in/zia-ur-rehman ↗ GitHub @ZiaUrRehman-bit ↗ Lero lero.ie/people/zia-ur-rehman ↗ Google Scholar View profile ↗