معرفی
Jamie Fairbrother is a Lecturer in Operational Research (Optimisation) at the Data Science Institute, Lancaster University, within the Department of Management Science. His research integrates optimisation, applied probability, and statistics to solve real-world problems in logistics and telecommunications, with a particular focus on stochastic programming and scenario generation.
Education: Jamie Fairbrother completed his PhD research in scenario generation for stochastic programming, which laid the foundation for his subsequent work in optimisation under uncertainty.
Research Interests: His expertise spans several domains:
- Optimisation & Operational Research: Development of mathematical models and algorithms for complex decision-making problems.
- Applied Probability & Statistics: Use of probabilistic methods to model uncertainty in planning and operations.
- Logistics & Telecommunications: Practical applications in mail centre staffing, airport slot scheduling, and wireless communication networks.
- Stochastic Programming: Scenario generation and robust optimisation techniques for strategic planning under uncertainty.
Research Funding & Projects: Dr Fairbrother has led or contributed to multiple collaborative projects, including:
- Coordination of Strategic and Tactical Interventions for Reducing Air Traffic Delays (2023–2024) – a case study at Heathrow Airport.
- STOR-i: Optimising In-Store Price Reductions (2022–2025) – with PhD student Katie Howgate.
- Resource Allocation under Uncertain Demand in Royal Mail Mail Centres (2020–2023).
- Industrial Mathematics KTP with BT Research (2013) – modelling TV whitespace interference.
PhD Supervision: He currently supervises Katie Howgate, a PhD student in Bayesian and Computational Statistics within the STOR-i Centre for Doctoral Training.
Professional Affiliations: Dr Fairbrother is affiliated with the STOR-i Centre for Doctoral Training, the Centre for Transport & Logistics (CENTRAL), and the OR-MASTER project on airport resource allocation.
