![Bahman Rostami-tabar](https://profiles-cardiff.imgix.net/attachments/4044?w=200&h=200&auto=format&crop=faces&fit=crop&q=90")
Dr Bahman Rostami-tabar
Reader in Data and Management Science
- Rostami-TabarB@cardiff.ac.uk
- +44 29208 70723
- Aberconway Building, Room Q08, Colum Road, Cathays, Cardiff, CF10 3EU
- Available for postgraduate supervision
Overview
Bahman is a Reader (Associate Professor) in Management Science & Business Analytics at Cardiff Business School, Cardiff University, UK.
He holds a Ph.D. in Industrial 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.
Bahman is the founder and Chair of Forecasting for Social Good initiatives sponsored by the International Institute of Forecasters. In his research, he has been developing and using management science and analytic tools and techniques to improve decision-making in healthcare, humanitarian operations and supply chain sectors. He has been working with many organisations including the National Health Service (NHS), Welsh Ambulance Service Trusts, United States Agency for International Developments and John Snow, Inc.
His research goals are directed toward the use of Management Science tools and techniques to improve decision making in supply chains and operations management, and as such positively contribute to both industrial and societal advancements.
Publication
2023
- 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., Juan F., R. and Goltsos, A. 2023. Probabilistic Forecasting of Daily COVID-19 Admissions using Machine Learning. IMA Journal of Management Mathematics
- 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
- Babaveisi, V., Teimoury, E., Gholamian, M. R. and Rostami-Tabar, B. 2022. Integrated demand forecasting and planning model for repairable spare part: an empirical investigation. International Journal of Production Research (10.1080/00207543.2022.2137596)
- 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., Babai, Z. and Syntetos, A. 2022. To aggregate or not to aggregate: Forecasting of finite autocorrelated demand. Journal of the Operational Research Society (10.1080/01605682.2022.2118631)
- 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)
Adrannau llyfrau
- 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
Cynadleddau
- 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)
Erthyglau
- 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., Juan F., R. and Goltsos, A. 2023. Probabilistic Forecasting of Daily COVID-19 Admissions using Machine Learning. IMA Journal of Management Mathematics
- 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)
- Babaveisi, V., Teimoury, E., Gholamian, M. R. and Rostami-Tabar, B. 2022. Integrated demand forecasting and planning model for repairable spare part: an empirical investigation. International Journal of Production Research (10.1080/00207543.2022.2137596)
- 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., Babai, Z. and Syntetos, A. 2022. To aggregate or not to aggregate: Forecasting of finite autocorrelated demand. Journal of the Operational Research Society (10.1080/01605682.2022.2118631)
- 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)
- 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
- Data Driven Forecasting (featured-based, Machine Learning)
- Time Series Forecasting
- Hierarchical and Temporal Aggregation
- Forecasting for Social Good
- Predictive modelling in healthcare
- Forecasting and Inventory Control in Supply Shain
- Forecasting and decision making
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., Industrial 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
- Predictive Modelling
- Time Series Forecasting
- Forecasting and Inventory Control in Supply Chain
- Forecasting by Aggregation
- Forecasting and Decision Making
- Analytics & policy
Applications are welcome in Healthcare, Humanitarian Operations, Supply Chain.
