The LCF consists of permanent members of staff, research staff and PhD students plus associated experts. In addition, the Centre is frequently visited by academics, researchers and PhD students to engage in mutual academic or corporate research activities.
Robert Fildes is Distinguished Professor of Management Science in the School of Management, Lancaster University and Director of the Lancaster Centre for Forecasting. He was co-founder in 1981 of the Journal of Forecasting and in 1985 of the International Journal of Forecasting. He has consulted and lectured widely on all aspects of the problem of improving forecasting in organisations. His major concern is that despite all the research, companies still stay with old-fashioned systems and methods. The solution, he thinks, is better designed forecasting systems and better trained forecasters.
Sven F Crone
Dr Sven F Crone is the director of the Lancaster Centre for Forecasting, and works as an Assistant Professor at Lancaster University Management School, UK. In addition to numerous publications in esteemed journals, Sven has over 15 years of expertise in corporate business forecasting.
He has widely consulted on corporate projects through the centre, in particular in supply chain forecasting for FMCG manufacturers, retail forecasting, as well as utilities and energy forecasting. His expertise ranges from improving software systems such as SAP APO-DP, to developing bespoke forecasting methods and model selection routines.
Sven has presented the Centre’s innovations and projects at 50+ international conferences, including keynotes at the SAS F2006 & F2008 forecasting and A2012 Analytics conferences, track speeches at APICS 2006 global conference, and annual appearances at IBF and ISF conferences. He frequently provides training courses for the centre, IBF and IEEE, educating over 400 demand planners on Forecasting Fundamentals,Statistical Forecasting with SAP APO-DP and Forecasting with Neural Networks all over the world.
John Boylan will join Lancaster University as Professor of Business Analytics in January 2015.
John has researched and taught in this area for over twenty years, having previously worked for seven years in industrial Operational Research groups. His research focuses on problems relating to the interface between demand forecasting and inventory management. His best known work is in intermittent demand forecasting, and he has advised software companies on the adoption of recent research developments into their packages.
John has served as a director of the International Institute of Forecasters and is currently a member of the Executive Committee of the International Society for Inventory Research.
Dr Nikolaos Kourentzes is an Assistant Professor in the department of Management Science, Lancaster University Management School. Nikos researches in several areas of business forecasting and his work has been presented in numerous international academic and practitioner conferences. He is regularly giving talks on improving and automating forecasting in organisations using established and state-of-the-art statistical methods. He has substantial experience in applied research projects with organisations in fast and slow moving consumer goods, advertising and media, retail and promotional modelling, new product forecasting and utilities energy forecasting. Nikos frequently provides training courses on business forecasting and demand planning, advanced statistical modelling, neural networks and SAP APO-DP.
Dr Nicos Pavlidis is a Lecturer (Assistant Professor) in the Lancaster University Management School. His has been active in the fields of data mining, time series forecasting, machine learning, and big data analytics. He has participated in a number of projects addressing complex real-world problems and collaborated with both academic and industrial partners. He has offered seminars and courses on forecasting and his research has been disseminated through major international conferences and leading journals.
Dr Gokhan Yildirim is an Assistant Professor in the department of Management Science at Lancaster University Management School. His research focuses on marketing productivity. Specifically, his approach emphasizes strategic marketing problems such as long-term marketing effectiveness, marketing resource allocation and marketing-finance interface. Methodologically, his research involves applied time series econometrics, in particular market-response modeling. He applied his expertise to fast moving consumer goods, kitchen appliances and textile sectors, among others.
Fahad H al-Qahtani is a PhD student in the Department of Management Science, sponsored by Saudi Aramco oil company. His research interests include machine learning, data mining and time series forecasting. He is currently focusing his research on the utilisation of active learning techniques for selecting the most informative examples for training time series forecasting models. Fahad holds a Masters degree in Computer Science from the University of Southern California and has worked as a system analyst in the oil and energy sector in the Middle East.
Lida Barakat is a PhD student in the Department of Management Science at Lancaster University Management School. She is working under the supervision of Dr Nicos Pavlidis and Dr Sven Crone on developing adaptive classification models for credit application scoring, which are able to react through appropriate learning, to changes in the classification data distribution occurring as a result of dynamic environment conditions. Lida also holds a MSc degree in Financial and Banking Sciences from Damascus University, and has special interest in developing data mining applications for supporting banking information systems.
Timo P Kunz
Timo P Kunz is a PhD student in Management Science at Lancaster University. During his undergraduate degree, pricing quickly became his main area of interest, getting him involved with companies such as Simon-Kucher & Partners, LVMH and Lufthansa Cargo. He then worked for 4.5 years as a consultant for SAP on retail pricing topics before joining Lancaster University and the Lancaster Centre for Forecasting. His current research interests centre on price optimization in retail and in particular the effects of data modelling choices in the retail price optimization system.
Oliver is a PhD student in the Department of Management Science, who joined following his MSc studies with the Department in 2013/14. His research explores the diffusion of online video content through social media platforms such as YouTube or Vimeo. Oliver aims to develop a model that can incorporate the viral nature of online media, which then allows the popularity prediction in terms of views of such content for a given time horizon on a cumulative basis. Other interests include machine learning, web analytics and the measurement of the ROI of corporate social media channels.
Ivan Svetunkov is a PhD student in Management Science at Lancaster University Management School. His main theme of interest is forecasting, specifically such forecasting methods as exponential smoothing and ARIMA and their different modifications. He is mostly interested in the application of forecasting methods to real business tasks. In his PhD he is working on a new type of exponential smoothing method that is called "Complex Exponential Smoothing" - CES.
Matt Weller is a PhD student in Management Science at Lancaster University Management School. His current research focuses on collaborative forecasting in the supply chain, firstly examining how firms are currently combining collaboration and forecasting in practice. The next phase of his research will be a modelling approach to examine which forecasting methods are most suited to alternative supply chain configurations and demand data properties. Prior to joining LCF, Matt worked in industry for 10 years as an IT consultant and has implemented planning solutions in several blue chip companies.
Gwern is a PhD student with the STOR-i Doctoral Training Centre.
His research is in the area of statistical modelling, specifically looking at models for low-count time-series. Gwern is supervised by Dr Nikos Kourentzes and Dr Peter Neal (Department of Mathematics and Statistics).
Gwern's current work aims to improve the existing state of knowledge on modelling and forecasting low-count time-series. The integer, non-negative and low-valued nature of low-count time-series present interesting but complex modelling challenges. Standard models for normal, continuous time-series, such as the popular ARIMA models, violate the properties of low-count time-series, and hence different models are needed. Gwern's research looks at integer models to address these issues.
Dr Fotios Petropoulos (University of Cardiff, UK)
Dr Juan Ramon Trapero Arenas (University Castilla La Mancha, Spain)
Dr Stavros Asimakopoulos (National & Kapodistrian University of Athens, Greece)
Dr Jessica (Tun-I) Hu
Dr Devon Barrow (Coventry University, UK)