About me

I am currently a Data Scientist (KTP Associate) for Knowledge Transfer Partnership (KTP) with the N/Lab and the Haydn Green Institute in the Nottingham University Business School and Strategic Innovation Limited. The aim of this project is to utilise cutting-edge AI and Big Data analytics to drive transformational change in the food production system, towards sustainability.

Come together for Food System Sustainability

Area of interests

Real world applications:

  • Challenges in Sustainable Food Systems
  • Transport Logistic Scheduling and Vehicle Routing Problems

AI Algorithms / techniques:

  • Machine Learning; Data Mining; Knowledge Explainability
  • Automated Algorithm Design; Hyper-heuristics; Evolutionary Computation; Combinatorial Optimisation

I completed my PhD at the Computational Optimization and Learning (COL) Lab.

My research interests focus on using AI techniques to support decision-making in sustainable development, particularly in domains such as sustainable transport, energy and food systems.

Quick links to Machine Learning Assisted Evolutionary Computation for Vehicle Routing Problems (ML4VRP)

Selected projects

I was a Research Assistant in the Amicable Charging (AMiCC) research project, delivering eco-friendly wireless charging solutions for electric vehicles, with a focus on optimizing the charging infrastructure. The project was led by Professor Lucelia Rodrigues (University of Nottingham).

I lead the completion of a KTP project as a KTP Associate to develop and deploy novel and advanced hyper-heuristics-based routing technologies for haulage markets. The project was led by Professor Ender Ozcan (University of Nottingham), Dr Ahmed Kheiri (Lancaster University), and Optrak, supported by KTP Scheme under Project No.KTP11692.


I was a Teaching Associate in the School of Computer Science at the University of Nottingham.

  • Course co-admin and instructor for the Heuristic Optimisation and Learning NATCOR course, 8-12 April 2024.
  • Co-conveyed the module Fundamentals of Artificial Intelligence (2023 spring).
  • Modules supported: Mathematics for Computer Scientists, Programming and Algorithms, Systems and Architecture, Computer Fundamentals, Operating Systems & Concurrency, Developing Maintainable Software, Simulation and Optimisation for Decision Support, Data Science and Machine Learning, and Machine Learning.