Seyedamirhossein Salehiamiri

Career Details

Amir is a Teaching Fellow in Business Analytics in the Department of Management Science at Lancaster University Management School. He teaches on Business Data and Intelligence, where he delivers the lectures on forecasting and data mining. Before joining Lancaster, Amir was a doctoral researcher and Graduate Teaching Fellow at Alliance Manchester Business School, The University of Manchester, where he is completing a journal-format PhD in Management Science and Marketing division.

Amir’s research develops optimisation methods for complex decision problems that have multiple conflicting objectives, uncertainty and demanding constraints. His PhD, “Decision support for smart home health care scheduling using wearable devices”, uses real-time data from Internet of Medical Things (IoMT) wearables to plan and adapt home care visits as patients’ needs change during the day. This work combines exact methods, such as mixed-integer linear programming and logic-based Benders decomposition, with stochastic optimisation and metaheuristics, and draws on a case study with a Manchester home care provider. His wider research covers sustainable and closed-loop supply chains, circular economy network design, Internet of Things (IoT) enabled logistics and multi-objective cybersecurity investment.

Amir's work has received over 1,000 citations on Google Scholar, and he won the Best Student Paper Award at the International Joint Conference on Computational Intelligence (IJCCI/ECTA) in 2024.

A key part of Amir’s work is turning real industry problems into formal models and practical decision tools. He currently collaborates with Dematic on warehouse automation. He has also worked with the Port of Dover on digital twin and dashboard development, with the Port of Aberdeen on berth allocation, with QCS on a scheduling app for home care, and with THG on cybersecurity investment planning.