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Professor Bahman Rostami-Tabar
(he/him)
Professor of Data-Driven Decision Science
- Rostami-TabarB@cardiff.ac.uk
- +44 29208 70723
- Aberconway Building, Room C08, Colum Road, Cathays, Cardiff, CF10 3EU
- Available for postgraduate supervision
Overview
Bahman is the Professor of Data-Driven Decision Science at Cardiff Business School, Cardiff University, UK.
Bahman is the founder and director of Data Lab for Social Good Research Group at Cardiff Business School and the founder and inaugural Chair of Forecasting for Social Good initiatives sponsored by the International Institute of Forecasters. Bahman specializes in the development and application of modelling, forecasting and management science tools and techniques providing informed insights for planning & decision-making processes in sectors contributing to social good, including healthcare operations, global health and humanitarian supply chains, agriculture and food, social sustainability, and governmental policy. His collaborative efforts have spanned a multitude of organisations, including notable bodies such as the National Health Service (NHS), Welsh Ambulance Service Trusts (WAST), United States Agency for International Developments (USAID), the International Committee of the Red Cross (ICRC), and John Snow Inc. (JSI). A remarkable highlight of his contributions is his pivotal role in disseminating forecasting knowledge especially in low and lower-middle income countries through the democratizing forecasting project sponsored by International Institute of Forecasters.
Bahman holds a Ph.D. in Production Engineering from the University of Bordeaux, France. He earned his B.Sc. in Industrial Engineering from K.N.Toosi University of Technology, Tehran, Iran, and his M.Sc. in Industrial Engineering from Tarbiat Modares University, Tehran.
Publication
2023
- Babaveisi, V., Teimoury, E., Gholamian, M. R. and Rostami-Tabar, B. 2023. Integrated demand forecasting and planning model for repairable spare part: an empirical investigation. International Journal of Production Research 61(20), pp. 6791-6807. (10.1080/00207543.2022.2137596)
- Rostami-Tabar, B. and Mircetic, D. 2023. Exploring the association between time series features and forecasting by temporal aggregation using machine learning. Neurocomputing 548, article number: 126376. (10.1016/j.neucom.2023.126376)
- Rostami-Tabar, B., Babai, Z. and Syntetos, A. 2023. To aggregate or not to aggregate: Forecasting of finite autocorrelated demand. Journal of the Operational Research Society 74(8), pp. 1840-1859. (10.1080/01605682.2022.2118631)
- Rostami-Tabar, B., Browell, J. and Svetunkov, I. 2023. Probabilistic forecasting of hourly Emergency Department arrivals. Health Systems (10.1080/20476965.2023.2200526)
- Rostami-Tabar, B., Arora, S., Rendon-Sanchez, J. F. and Goltsos, T. E. 2023. Probabilistic forecasting of daily COVID-19 admissions using machine learning. IMA Journal of Management Mathematics (10.1093/imaman/dpad009)
- Abolghasemi, M., Rostami-Tabar, B. and Syntetos, A. 2023. The value of point of sales information in upstream supply chain forecasting: an empirical investigation. International Journal of Production Research 61(7), pp. 2162-2177. (10.1080/00207543.2022.2063086)
- Rostami-Tabar, B. and Disney, S. 2023. On the order-up-to policy with intermittent integer demand and logically consistent forecasts. International Journal of Production Economics 257, article number: 108763. (10.1016/j.ijpe.2022.108763)
- Rostami-Tabar, B., Goltsos, T. E. and Shixuan, W. 2023. Forecasting for lead-time period by temporal aggregation: Whether to combine and how. Computers in Industry 145, article number: 103803. (10.1016/j.compind.2022.103803)
2022
- Rostami-Tabar, B., Hasni, M. and Babai, Z. 2022. On the inventory performance of demand forecasting methods of medical items in humanitarian operations. IFAC-PapersOnLine 55(10), pp. 2737-2742. (10.1016/j.ifacol.2022.10.132)
- Gartner, D., Viana, J., Rostami-Tabar, B., Pförringer, D. and Edenharter, G. 2022. Challenging the throwaway culture in hospitals: scheduling the mix of reusable and single-use bronchoscopes. Journal of the Operational Research Society (10.1080/01605682.2022.2129490)
- Rostami-Tabar, B. and Ziel, F. 2022. Anticipating special events in emergency department forecasting. International Journal of Forecasting 38(3), pp. 1197-1213. (10.1016/j.ijforecast.2020.01.001)
- Rostami-Tabar, B., Ali, M. M., Hong, T., Hyndman, R. J., Porter, M. D. and Syntetos, A. 2022. Forecasting for social good. International Journal of Forecasting 38(3), pp. 1245-1257. (10.1016/j.ijforecast.2021.02.010)
- Petropoulos, F. et al. 2022. Forecasting: theory and practice. International Journal of Forecasting 38(8), pp. 705-871. (10.1016/j.ijforecast.2021.11.001)
- Rostami-Tabar, B. and Boylan, J. 2022. Forecasting and its Beneficiaries. In: Salhi, S. and Boylan, J. eds. The Palgrave Handbook of Operations Research. Palgrave Macmillan, pp. 695-717., (10.1007/978-3-030-96935-6_21)
- Rostami-Tabar, B., Hong, T. and Porter, M. D. 2022. Guest Editorial: Forecasting for social good. International Journal of Forecasting 38(3), pp. 1173-1174.
- Mircetic, D., Rostami-Tabar, B., Nikolicic, S. and Maslaric, M. 2022. Forecasting hierarchical time series in supply chains: an empirical investigation. International Journal of Production Research 60(8), pp. 2514-2533. (10.1080/00207543.2021.1896817)
- Babai, M. Z., Boylan, J. E. and Rostami-Tabar, B. 2022. Demand forecasting in supply chains: a review of aggregation and hierarchical approaches. International Journal of Production Research 60(1), pp. 324-348. (10.1080/00207543.2021.2005268)
- Wang, Z., Rostami-Tabar, B., Haider, J. J. and Naim, M. 2022. A systematic literature review of trauma networks and systems: from operations management perspectives. Presented at: 12th European Decision Sciences Conference, Dublin, Ireland, 29 May – 1 June 2022.
2021
- Rostami-Tabar, B. 2021. Business forecasting in developing countries. In: Gilliland, M., Tashman, L. and Sglavo, U. eds. Business forecasting : the emerging role of artificial intelligence and machine learning. Wiley and SAS Business Series
- Rostami-Tabar, B. and Rendon-Sanchez, J. F. 2021. Forecasting COVID-19 daily cases using phone call data. Applied Soft Computing 100, article number: 106932. (10.1016/j.asoc.2020.106932)
2019
- Rostami-Tabar, B., Babai, M. Z., Ali, M. and Boylan, J. E. 2019. The impact of temporal aggregation on supply chains with ARMA(1,1) demand processes. European Journal of Operational Research 273(3), pp. 920-932. (10.1016/j.ejor.2018.09.010)
2017
- Kourentzes, N., Rostami-Tabar, B. and Barrow, D. K. 2017. Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?. Journal of Business Research 78 (10.1016/j.jbusres.2017.04.016)
- Rostami-Tabar, B. and Disney, S. M. 2017. The bullwhip effect under count time series: The case of first order integer auto-regressive demand processes. Presented at: International Symposium on Industrial Engineering and Operations Management, Bristol, UK, 25-26 July 2017.
- Rostami-Tabar, B. and Disney, S. M. 2017. The impact of temporal aggregation on production and inventory costs. Presented at: OR59 Annual Conference, Loughborough, United Kingdom, 12-14 September 2017.
2016
- Emrouznejad, A., Rostami-Tabar, B. and Petridis, K. 2016. A novel ranking procedure for forecasting approaches using data envelopment analysis. Technological Forecasting and Social Change 111, pp. 235-243. (10.1016/j.techfore.2016.07.004)
2015
- Rostami-Tabar, B., Babai, M. Z., Ducq, Y. and Syntetos, A. 2015. Non-stationary demand forecasting by cross-sectional aggregation. International Journal of Production Economics 170(Part A), pp. 297-309. (10.1016/j.ijpe.2015.10.001)
2014
- Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2014. A note on the forecast performance of temporal aggregation. Naval Research Logistics 61(7), pp. 489-500. (10.1002/nav.21598)
2013
- Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2013. Demand forecasting by temporal aggregation. Naval Research Logistics 60(6), pp. 479-498. (10.1002/nav.21546)
2008
- Amin-Naseri, M. and Rostami-Tabar, B. 2008. Neural network approach to lumpy demand forecasting for spare parts in process industries. Presented at: International Conference on Computer and Communication Engineering, 13-15 May 20082008 International Conference on Computer and Communication Engineering Proceedings. IEEE pp. -., (10.1109/ICCCE.2008.4580831)
- Nasiri Pour, A., Rostami-Tabar, B. and Rahimzadeh, A. 2008. A hybrid neural network and traditional approach for forecasting lumpy demand. Proceedings of the World Academy of Science, Engineering and Technology 2(4)
Articles
- Babaveisi, V., Teimoury, E., Gholamian, M. R. and Rostami-Tabar, B. 2023. Integrated demand forecasting and planning model for repairable spare part: an empirical investigation. International Journal of Production Research 61(20), pp. 6791-6807. (10.1080/00207543.2022.2137596)
- Rostami-Tabar, B. and Mircetic, D. 2023. Exploring the association between time series features and forecasting by temporal aggregation using machine learning. Neurocomputing 548, article number: 126376. (10.1016/j.neucom.2023.126376)
- Rostami-Tabar, B., Babai, Z. and Syntetos, A. 2023. To aggregate or not to aggregate: Forecasting of finite autocorrelated demand. Journal of the Operational Research Society 74(8), pp. 1840-1859. (10.1080/01605682.2022.2118631)
- Rostami-Tabar, B., Browell, J. and Svetunkov, I. 2023. Probabilistic forecasting of hourly Emergency Department arrivals. Health Systems (10.1080/20476965.2023.2200526)
- Rostami-Tabar, B., Arora, S., Rendon-Sanchez, J. F. and Goltsos, T. E. 2023. Probabilistic forecasting of daily COVID-19 admissions using machine learning. IMA Journal of Management Mathematics (10.1093/imaman/dpad009)
- Abolghasemi, M., Rostami-Tabar, B. and Syntetos, A. 2023. The value of point of sales information in upstream supply chain forecasting: an empirical investigation. International Journal of Production Research 61(7), pp. 2162-2177. (10.1080/00207543.2022.2063086)
- Rostami-Tabar, B. and Disney, S. 2023. On the order-up-to policy with intermittent integer demand and logically consistent forecasts. International Journal of Production Economics 257, article number: 108763. (10.1016/j.ijpe.2022.108763)
- Rostami-Tabar, B., Goltsos, T. E. and Shixuan, W. 2023. Forecasting for lead-time period by temporal aggregation: Whether to combine and how. Computers in Industry 145, article number: 103803. (10.1016/j.compind.2022.103803)
- Rostami-Tabar, B., Hasni, M. and Babai, Z. 2022. On the inventory performance of demand forecasting methods of medical items in humanitarian operations. IFAC-PapersOnLine 55(10), pp. 2737-2742. (10.1016/j.ifacol.2022.10.132)
- Gartner, D., Viana, J., Rostami-Tabar, B., Pförringer, D. and Edenharter, G. 2022. Challenging the throwaway culture in hospitals: scheduling the mix of reusable and single-use bronchoscopes. Journal of the Operational Research Society (10.1080/01605682.2022.2129490)
- Rostami-Tabar, B. and Ziel, F. 2022. Anticipating special events in emergency department forecasting. International Journal of Forecasting 38(3), pp. 1197-1213. (10.1016/j.ijforecast.2020.01.001)
- Rostami-Tabar, B., Ali, M. M., Hong, T., Hyndman, R. J., Porter, M. D. and Syntetos, A. 2022. Forecasting for social good. International Journal of Forecasting 38(3), pp. 1245-1257. (10.1016/j.ijforecast.2021.02.010)
- Petropoulos, F. et al. 2022. Forecasting: theory and practice. International Journal of Forecasting 38(8), pp. 705-871. (10.1016/j.ijforecast.2021.11.001)
- Rostami-Tabar, B., Hong, T. and Porter, M. D. 2022. Guest Editorial: Forecasting for social good. International Journal of Forecasting 38(3), pp. 1173-1174.
- Mircetic, D., Rostami-Tabar, B., Nikolicic, S. and Maslaric, M. 2022. Forecasting hierarchical time series in supply chains: an empirical investigation. International Journal of Production Research 60(8), pp. 2514-2533. (10.1080/00207543.2021.1896817)
- Babai, M. Z., Boylan, J. E. and Rostami-Tabar, B. 2022. Demand forecasting in supply chains: a review of aggregation and hierarchical approaches. International Journal of Production Research 60(1), pp. 324-348. (10.1080/00207543.2021.2005268)
- Rostami-Tabar, B. and Rendon-Sanchez, J. F. 2021. Forecasting COVID-19 daily cases using phone call data. Applied Soft Computing 100, article number: 106932. (10.1016/j.asoc.2020.106932)
- Rostami-Tabar, B., Babai, M. Z., Ali, M. and Boylan, J. E. 2019. The impact of temporal aggregation on supply chains with ARMA(1,1) demand processes. European Journal of Operational Research 273(3), pp. 920-932. (10.1016/j.ejor.2018.09.010)
- Kourentzes, N., Rostami-Tabar, B. and Barrow, D. K. 2017. Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?. Journal of Business Research 78 (10.1016/j.jbusres.2017.04.016)
- Emrouznejad, A., Rostami-Tabar, B. and Petridis, K. 2016. A novel ranking procedure for forecasting approaches using data envelopment analysis. Technological Forecasting and Social Change 111, pp. 235-243. (10.1016/j.techfore.2016.07.004)
- Rostami-Tabar, B., Babai, M. Z., Ducq, Y. and Syntetos, A. 2015. Non-stationary demand forecasting by cross-sectional aggregation. International Journal of Production Economics 170(Part A), pp. 297-309. (10.1016/j.ijpe.2015.10.001)
- Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2014. A note on the forecast performance of temporal aggregation. Naval Research Logistics 61(7), pp. 489-500. (10.1002/nav.21598)
- Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2013. Demand forecasting by temporal aggregation. Naval Research Logistics 60(6), pp. 479-498. (10.1002/nav.21546)
- Nasiri Pour, A., Rostami-Tabar, B. and Rahimzadeh, A. 2008. A hybrid neural network and traditional approach for forecasting lumpy demand. Proceedings of the World Academy of Science, Engineering and Technology 2(4)
Book sections
- Rostami-Tabar, B. and Boylan, J. 2022. Forecasting and its Beneficiaries. In: Salhi, S. and Boylan, J. eds. The Palgrave Handbook of Operations Research. Palgrave Macmillan, pp. 695-717., (10.1007/978-3-030-96935-6_21)
- Rostami-Tabar, B. 2021. Business forecasting in developing countries. In: Gilliland, M., Tashman, L. and Sglavo, U. eds. Business forecasting : the emerging role of artificial intelligence and machine learning. Wiley and SAS Business Series
Conferences
- Wang, Z., Rostami-Tabar, B., Haider, J. J. and Naim, M. 2022. A systematic literature review of trauma networks and systems: from operations management perspectives. Presented at: 12th European Decision Sciences Conference, Dublin, Ireland, 29 May – 1 June 2022.
- Rostami-Tabar, B. and Disney, S. M. 2017. The bullwhip effect under count time series: The case of first order integer auto-regressive demand processes. Presented at: International Symposium on Industrial Engineering and Operations Management, Bristol, UK, 25-26 July 2017.
- Rostami-Tabar, B. and Disney, S. M. 2017. The impact of temporal aggregation on production and inventory costs. Presented at: OR59 Annual Conference, Loughborough, United Kingdom, 12-14 September 2017.
- Amin-Naseri, M. and Rostami-Tabar, B. 2008. Neural network approach to lumpy demand forecasting for spare parts in process industries. Presented at: International Conference on Computer and Communication Engineering, 13-15 May 20082008 International Conference on Computer and Communication Engineering Proceedings. IEEE pp. -., (10.1109/ICCCE.2008.4580831)
- Kourentzes, N., Rostami-Tabar, B. and Barrow, D. K. 2017. Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?. Journal of Business Research 78 (10.1016/j.jbusres.2017.04.016)
- Rostami-Tabar, B. and Disney, S. M. 2017. The bullwhip effect under count time series: The case of first order integer auto-regressive demand processes. Presented at: International Symposium on Industrial Engineering and Operations Management, Bristol, UK, 25-26 July 2017.
- Rostami-Tabar, B. and Disney, S. M. 2017. The impact of temporal aggregation on production and inventory costs. Presented at: OR59 Annual Conference, Loughborough, United Kingdom, 12-14 September 2017.
- Emrouznejad, A., Rostami-Tabar, B. and Petridis, K. 2016. A novel ranking procedure for forecasting approaches using data envelopment analysis. Technological Forecasting and Social Change 111, pp. 235-243. (10.1016/j.techfore.2016.07.004)
- Rostami-Tabar, B., Babai, M. Z., Ducq, Y. and Syntetos, A. 2015. Non-stationary demand forecasting by cross-sectional aggregation. International Journal of Production Economics 170(Part A), pp. 297-309. (10.1016/j.ijpe.2015.10.001)
- Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2014. A note on the forecast performance of temporal aggregation. Naval Research Logistics 61(7), pp. 489-500. (10.1002/nav.21598)
- Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2013. Demand forecasting by temporal aggregation. Naval Research Logistics 60(6), pp. 479-498. (10.1002/nav.21546)
Research
Research
I am interested in developing innovative methodologies in forecasting for social goo and how forecasting, nowcasting and .
Primary research interests
- Forecasting for Social Good
- Healthcare operations
- Global health and Humanitarian operations
- Data Driven Forecasting (featured-based, Machine Learning)
- Machine learning
- Decision Science
Teaching
Teaching commitments
- Forecasting
- Business Data Analytics
- Healthcare Planning Evidence & Analytics
- Inventory Management
- Supply Chain Planning
I have been delivering trainings on Data Analytics and Forecasting using R since 2018. I have trained over 500 people in the UK (mainly NHS analysts), Tunisia, Senegal, Nigeria, Uganda, Iraq, Turkey, Indonesia and Georgia so far. My trainings cover various topics including how to prepare, manipulate and visualize data, apply various forecasting models and evaluate their forecast accuacy in R.
If you need a training in these areas, get in touch.
Biography
Qualifications
- 2016 - Postgraduate Certificate in Learning and Teaching in Higher Education, Coventry University, UK
- 2014 - Ph.D., Production Engineering. Thesis entitled 'ARIMA Demand Forecasting by Aggregation', University of Bordeaux, France
- 2010 - M.Sc., Information Systems, ECE Paris, France
- 2009 - Proficiency in French Language, Université de Poitiers , France
- 2008 - M.Sc., Industrial Engineering, Tarbiat Modares University, Tehran, Iran
- 2002 - B.Sc., Industrial Engineering, K.N.Toosi Uni. Of Technology, Tehran, Iran (4 years).
Honours and awards
- 2009 - 2013 Campus France Scholarship award
- 2013 MIM best paper award (IFAC)
- 2017 International Symposium on Industrial Engineering and Operations Management, Best Track Paper Award, Bristol, UK
Academic positions
- 2015 - 2016: Lecturer in Supply Chain Management, School of Strategy and Leadership, Coventry University, UK.
- 2013 - 2015: Postdoctoral Research Fellowship, Industrial Engineering Lab, Ecole Centrale Paris, France.
Supervisions
PhD Supervision
I welcome enquiries from potential PhD students in the areas of
- Forecasting for Social Good
- Healthcare Operations
- Global Health and Humanitarian Supply Chain
- Data Science and Machine Learning in healthcare and policy
- Time Series Forecasting
- Forecasting by Aggregation (Hierarchical and temporal)
Current supervision
Research themes
Specialisms
- Time Series Forecasting
- Machine learning
- Data-Driven Decision Science
- Forecasting for Social Good
- Hierarchical and Temporal Forecast Reconciliation
