School of Mathematics and Physics

Dr Mahdi Abolghasemi

Lecturer
Mathematics
Priestley Building (67), Room 555
View researcher profile

Researcher biography

Dr Abolghasemi has a multi-disciplinary background in Engineering, Business, Statistics, and Machine Learning. His research interests/expertise are in time series forecasting, predictive analytics, data science, and machine learning with applications in supply chain management, and renewable energies optimisation. Through his research, Dr Abolghasemi has consulted dozens of companies in Australia, Europe and the Middle East and developed several analytical models to improve their supply chain networks and analytical capabilities. Dr Abolghasemi's research is closely tied to evidence-based analytics for real-world problems. He has published over 40 articles and technical reports and presented at numerous national and international conferences.

Mahdi is a consultant and member of the International Institute of Forecasters, the Australian Mathematical Society, and INFORMS. He serves on the editorial board of the International Journal of Forecasting and is a regular reviewer of the International Journal of Production Economics, the International Journal of Production Research, and several international conferences. Dr Abolghasemi is the founding chair and host of an international scientific podcast, Forecasting Impact which has audiences in over 110 countries around the world.

Dr Abolghasemi is a passionate teacher and thought leader in higher education. He has studied and worked on three continents. He shares his experience by supervising talented young students and helping them to achieve their goals.

Featured projects Duration
Predicting the solutions of optimisation models with machine learning
Hierarchical forecasting with constrained optimisation
Optimisation of frameworks for development and operation of automated sound classification in real-world environmental monitoring
Graph Neural Network for Hierarchical Time Series Forecasting
Using Constrained Optimisations in Hierarchical Time Series Forecasting
Predict and optimise

Publications

Journal Articles (10)
Conference Papers (2)

Journal Articles

Abolghasemi, Mahdi, Tarr, Garth and Bergmeir, Christoph (2022). Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions. International Journal of Forecasting. doi: 10.1016/j.ijforecast.2022.07.004
Abolghasemi, Mahdi, Rostami-Tabar, Bahman and Syntetos, Aris (2022). The value of point of sales information in upstream supply chain forecasting: an empirical investigation. International Journal of Production Research, 61 (7), 1-16. doi: 10.1080/00207543.2022.2063086
Abolghasemi, Mahdi, Hyndman, Rob J., Spiliotis, Evangelos and Bergmeir, Christoph (2022). Model selection in reconciling hierarchical time series. Machine Learning, 111 (2), 739-789. doi: 10.1007/s10994-021-06126-z
Spiliotis, Evangelos, Abolghasemi, Mahdi, Hyndman, Rob J., Petropoulos, Fotios and Assimakopoulos, Vassilios (2021). Hierarchical forecast reconciliation with machine learning. Applied Soft Computing, 112 107756, 107756. doi: 10.1016/j.asoc.2021.107756
Abolghasemi, Mahdi, Hurley, Jason, Eshragh, Ali and Fahimnia, Behnam (2020). Demand forecasting in the presence of systematic events: cases in capturing sales promotions. International Journal of Production Economics, 230. doi: 10.1016/j.ijpe.2020.107892
Zamani, Mohsen, Abolghasemi, Mahdi, Hosseini, Seyed Mohammad Seyed and Pishvaee, Mir Saman (2020). Considering pricing and uncertainty in designing a reverse logistics network. International Journal of Industrial and Systems Engineering, 35 (2), 158-182. doi: 10.1504/IJISE.2020.107554
Abolghasemi, Mahdi, Beh, Eric, Tarr, Garth and Gerlach, Richard (2020). Demand forecasting in supply chain: the impact of demand volatility in the presence of promotion. Computers & Industrial Engineering, 142 106380, 106380. doi: 10.1016/j.cie.2020.106380
Alizadeh, Reza, Lund, Peter D., Beynaghi, Ali, Abolghasemi, Mandi and Maknoon, Reza (2016). An integrated scenario-based robust planning approach for foresight and strategic management with application to energy industry. Technological Forecasting and Social Change, 104, 162-171. doi: 10.1016/j.techfore.2015.11.030
Abolghasemi, Mahdi, Khodakarami, Vahid and Tehranifard, Hamid (2015). A new approach for supply chain risk management: mapping SCOR into Bayesian network. Journal of Industrial Engineering and Management, 8 (1), 280-302. doi: 10.3926/jiem.1281
Abolghasemi, Mahdi and Alizadeh, Reza (2014). A Bayesian framework for strategic management in energy industry. International Journal of Science, Engineering and Technology, 3 (11), 1360-1366.

Conference Papers

Hamza, M., Abolghasemi, M. and Alvandi, A.O. (2021). Forecasting sales with Bayesian networks: a case study of a supermarket product in the presence of promotions. Modeling and Simulation Conference (MODSIM), Sydney, Australia, 5-10 December 2021. Modelling and Simulation Society of Australia and New Zealand. doi: 10.36334/modsim.2021.M9.hamza
Abolghasemi, Mahdi and Khodakarami, Vahid (2014). Measuring down stream supply chain performance using Bayesian network. 44th International Conference of Computer and Industrial Engineering, Istanbul, Turkey, 14-16 October 2014. Los Angeles, CA, United States: Computers and Industrial Engineering.

Areas of research

Statistics, probability and data science