Dr Bahman Rostami-Tabar
Senior Lecturer in Management Science
- rostami-tabarb@cardiff.ac.uk
- +44 (0)29 2087 0723
- C08, Aberconway Building, Colum Road, Cathays, Cardiff, CF10 3EU
- Available for postgraduate supervision
Overview
Bahman is Senior Lecturer (Associate Professor) in Management Science at Cardiff Business School, Cardiff University.
Bahman holds a Ph.D. in Industrial Engineering from the University of Bordeaux. 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.
His research goals are directed toward the use of Operations Research (OR) techniques to improve decision making in supply chains and operations management (SCOM), and as such positively contribute to both industrial and societal advancements.
Biography
Qualifications
- 2016 - Postgraduate Certificate in Learning and Teaching in Higher Education, Coventry University, UK
- 2013 - 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.
Publications
2021
- Babai, M. Z., Boylan, J. E. and Rostami-Tabar, B. 2021. Demand forecasting in supply chains: a review of aggregation and hierarchical approaches. International Journal of Production Research (10.1080/00207543.2021.2005268)
- Petropoulos, F.et al. 2021. Forecasting: theory and practice. International Journal of Forecasting
- 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)
- Rostami-Tabar, B.et al. 2021. Forecasting for social good. International Journal of Forecasting (10.1016/j.ijforecast.2021.02.010)
- Mircetic, D.et al. 2021. Forecasting hierarchical time series in supply chains: an empirical investigation. International Journal of Production Research (10.1080/00207543.2021.1896817)
2020
- Rostami-Tabar, B. and Ziel, F. 2020. Anticipating special events in emergency department forecasting. International Journal of Forecasting (10.1016/j.ijforecast.2020.01.001)
2019
- Rostami-Tabar, B.et al. 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.et al. 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.et al. 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.et al. 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)
Teaching
Teaching commitments
- Forecasting
- Business Data Analytics
- Healthcare Planning Evidence & Analytics
Research
I am interested in research on time series forecasting, and developing innovative methodologies in forecasting for social good. In my research, I have examined how a data transformation apparoach (Temporal Aggregation) can improve forecast accuracy and utilities. I am currently working on projects which are concerned with the social impact of forecasting.
Primary research interests
- Predictive modelling
- Forecasting
- Forecasting for social good (health, Humanitarian, enviroment, education,...)
- The interface between forecasting and decision makin
Supervision
PhD Supervision
I welcome enquiries from potential PhD students in the areas of
- Forecasting/prediction
- Time Series Forecasting
- Forecasting for Social Good
- Predictive modelling in healthcare
- Forecasting and Inventory Control in Supply Shain
- Forecasting by Aggregation
- Forecasting and decision making
