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  • Riccarton

    EH14 4AS Edinburgh

    United Kingdom

20142025

Research activity per year

Personal profile

Research interests

Specialising in Operations Research (OR), Machine Learning (ML), and optimisation for logistics and supply chain systems, with a proven track record of developing decision-support tools for sustainable freight operations. Developed the Domino Algorithm, a novel optimisation methodology published in 2019, and has since applied advanced metaheuristics, machine learning, and simulation modelling to support Total Cost of Ownership (TCO) analysis and decarbonisation strategies across last-mile and long-haul road freight. Current research focuses on bi-level agent learning frameworks for modelling stakeholder decision-making during transport and logistics transitions. Combines strong technical research expertise with industry-facing project leadership, supported by an active Project Management Professional (PMP) certification since 2012.

Education/Academic qualification

Doctor of Engineering, Enhancing the Bees Algorithm using the traplining metaphor, University of Birmingham

Award Date: 6 Dec 2021

Master of Engineering, Improvement Model of Assembly Location Evaluation in Multi-Plant Assembly Planning, Institute of Technology Bandung

Award Date: 1 Feb 2009

Bachelor of Engineering, Design and Development of Electrical Connection Device with QFD Method, Universitas Gadjah Mada

Award Date: 1 Nov 2004

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

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