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

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.

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, pp. 1-9. (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 commitments

Forecasting
Risk Management in Supply Chains

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

Forecasting for social good (health, Humanitarian, enviroment, education,...)
The interface between forecasting and decision makin

PhD Supervision

I welcome enquiries from potential PhD students in the areas of forecasting for social good (health, humanitarian operations, education, ...) and Forecasting by aggregation.