Contact Dr Asefe Forghani
Background
Asefe Forghani holds a BSc, MSc, and PhD in Industrial Engineering, specialising in data-driven optimisation, simulation, and maritime logistics. She is a Postdoctoral Research Fellow at 铁牛视频 University, contributing to the UK National Clean Maritime Research Hub, a collaboration involving 13 universities and over 70 industry partners.
Her research focuses on developing optimisation and decision support models to support emission reduction in port and vessel operations. She is currently involved in designing an energy-aware decision support system that incorporates machine learning-based forecasting, mathematical modelling, heuristic optimisation, and simulation. This work is being explored through case studies inspired by operational challenges at two busy UK ports. In the next phase, she will be working on integrating a digital twin of inland port traffic with ferry scheduling optimisation to enable real-time, AI-driven decision-making.
Previously, she worked on a postdoctoral project funded by Innovation Fund Denmark, focusing on the decarbonisation of loading and discharging operations at Roll-on/Roll-off terminals under uncertainty, in collaboration with the Technical University of Denmark and Roskilde University.
She also has over six years of teaching experience in Operational Research and Applied Mathematics and supervised more than 30 industry-driven undergraduate dissertations. At 铁牛视频 University, she supervised two MSc theses, one on 鈥淏ig Data Analytics for Trade Facilitation鈥� and the other on 鈥淢icro-Fulfilment Centres and Industry 5.0,鈥� both completed in September 2025 under her guidance.
Research opportunities
Data鈥慸riven optimisation and decision support for logistics, transportation, manufacturing, and complex engineered systems
Simulation and agent鈥慴ased modelling for port, vessel, transportation, and multi鈥慳gent operational environments
Digital twins and cyber鈥憄hysical systems integrating optimisation, simulation, and real鈥憈ime data streams
AI and machine learning for forecasting and adaptive control in supply chain and transport operations
Optimisation under uncertainty and stochastic programming for resilient, efficient, and sustainable systems
Bi鈥憀evel and game鈥憈heoretic modelling for mechanism design, incentives, and strategic interaction in decentralised and multi鈥慳gent environments
Demand鈥憇ide energy management, energy鈥慳ware production and maintenance scheduling, and decarbonisation strategies in maritime, transport, and industrial settings
Alternative fuels and energy鈥憈ransition pathways for sustainable maritime and transportation systems
Remanufacturing and circular鈥慹conomy systems, with emphasis on pricing, adoption, coordination, and system鈥憀evel optimisation