UCL School of Management

Karima Dyussekeneva

Lecturer (Education)
Office location
Level 50, 1 Canada Square
Rm 56 Canary Wharf, London E14 5AA

Biography

Dr. Karima Dyussekeneva is a lecturer (education) at the UCL School of Management. Director of the Analytics Lab as a programme enrichment activity. She has a PhD in Information Decision Making from the University of Bath, with a thesis that explored methods of new product forecasting and empirically investigated quantitative and qualitative forecasting instruments.

She also holds an MBA from Durham University. Prior to entering academia, she worked in the telecommunications industry in domains including new product development, sales forecasting and marketing analysis. She advised a number of organisations and companies, including major international brands, in both the public and private sector in forecasting and predictive analytics.

Her current research interests focus on predictive analytics and data mining, machine learning and artificial intelligence, forecasting, decision making and business analytics in the interdisciplinary fields of management, computer science, finance and healthcare.

Research

Currently working on research projects: i) financial investment predictive analytics, scenarios of outcome; ii) consumer behaviour and virtual reality in retail industry; iii) predictive analytics in neurological diseases; iv) ethical AI (Artificial Intelligence).
Selected publications
Goodwin, P., Meeran, S., & Dyussekeneva, K. (2014). The challenges of pre-launch forecasting of adoption time series for new durable products. INTERNATIONAL JOURNAL OF FORECASTING, 30 (4), 1082-1097. doi:10.1016/j.ijforecast.2014.08.009 [link]
Meeran, S., Dyussekeneva, K., & Goodwin, P. (2013). Sales forecasting using combination of diffusion model and forecast market – an adaption of prediction/preference markets. IFAC Proceedings Volumes, 46 (9), 87-92. doi:10.3182/20130619-3-ru-3018.00619 [link]
Goodwin, P., Dyussekeneva, K., & Meeran, S. (2013). The use of analogies in forecasting the annual sales of new electronics products. IMA JOURNAL OF MANAGEMENT MATHEMATICS, 24 (4), 407-422. doi:10.1093/imaman/dpr025 [link]