Seyed is currently Programme Director for the MSc Business Analytics. He received his PhD from Southampton Business School in 2022 and an MSc in Engineering Business Management from the University of Sussex in 2015.
His doctoral research focused on the safety assessment and risk analysis of AI-based autonomous systems and their applications in urban environments. In 2022, he undertook a PhD placement at the Centre for Connected and Autonomous Vehicles (CCAV), where he investigated the potential impacts of connected and autonomous vehicles on carbon emissions within road transport.
Prior to this, he joined Northumbria University in 2021 as a Research Fellow, contributing to projects on the integration of AI and Big Data Analytics into the UK automotive sector’s logistics and supply chain systems, with a particular focus on inventory management.
Alongside his academic career, he has several years of industry experience as a project manager and strategy analyst.
Research Interests:
Risk Analytics for socio-technical and cyber-physical systems
Applications of evolutionary algorithms in optimisation and OR
Causal inference and expert elicitation for uncertainty modelling
User acceptance and adoption of disruptive technologies
Operations and innovation management in the Industry 5.0 era
Article
Skoumpopoulou D, Toliyat SMH, Ojra A, Shokri A & Hu S (2024) Challenges of achieving digital transformation in manufacturing firms: the case of predictive maintenance and spare part inventory management Journal of Manufacturing Technology Management. Journal of Manufacturing Technology Management. https://doi.org/10.1108/JMTM-04-2024-0211
Article
Shokri A, Toliyat SMH, Hu S & Skoumpopoulou D (2024) Integrating spare part inventory management and predictive maintenance as a digital supply chain solution. Journal of Modelling in Management. https://doi.org/10.1108/JM2-05-2024-0131
Conference Paper (published)
An Extension to the Traditional Technology Acceptance Model (TAM) for Semi-Autonomous Vehicles
Toliyat SMH (2023) An Extension to the Traditional Technology Acceptance Model (TAM) for Semi-Autonomous Vehicles. In: 8th Humanist Conference, Berlin, Germany, 21.09.2023-22.09.2023, pp. 147-153. https://www.humanist-vce.eu/proceedings-conferences
Conference Paper (published)
Toliyat SMH, Remfry C & Levi I (2023) Investigating the impacts of connected and automated vehicles on road carbon emissions: A semi-systematic literature review. In: , 13.07.2022, pp. 25-31. https://doi.org/10.55066/proc-icec.2022.58
Conference Paper (unpublished)
Shokri A & Toliyat SMH (2022) Assessing integration of spare part inventory management and predictive maintenance as a digital supply chain solution in automotive supply chain., 01.07.2022.
Project Report
The future of connected and automated mobility in the UK: call for evidence
Ramchurn S, Mousavi MR, Toliyat SMH, Kleinman M, Lisinska J, Stein S, Gerding E, Gomer R & D'Amore F (2021) The future of connected and automated mobility in the UK: call for evidence. Centre for Connected and Autonomous Vehicles. https://doi.org/10.5258/SOTON/P0097
MANP001 - Fundamentals of Business Analytics
MANP007 - Digital Business and Data Technologies
MANU9IM - Innovation Management
