Bahman Rostami-Tabar

Bahman is Senior Lecturer (Associate Professor) in Management Science at Cardiff Business School, Cardiff University.

Bahman's life objective is to help the world becoming a better place by freely offering his skills and developing free resources.

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.

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

• Rostami-Tabar, B. and Ziel, F. 2020. Anticipating special events in emergency department forecasting. International Journal of Forecasting
• 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.
• 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
• 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.
• 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.
• Rostami-Tabar, B.et al. 2014. A note on the forecast performance of temporal aggregation. Naval Research Logistics 61(7), pp. 489-500.
• Rostami-Tabar, B.et al. 2013. Demand forecasting by temporal aggregation. Naval Research Logistics 60(6), pp. 479-498.
• 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.
• 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)