Prior to joining the Management School as University Teacher in Digital Information Innovation and Management, I have completed my MBA and PhD here. Before returning to academia, I have spent several years running my own IT consultancy firm with focus on business information systems and automated decision making.
I believe my combination of practical and academic experience places me well to make a valuable contribution to Operations Management and Decision Sciences Division and in particular to prepare taught students for the real business challenges. I continuously pursue innovation in research and teaching and in respect of my industry experience, I trust that is crucially important for the competitive learning and working ethos I seek to provide to students. Maintaining an active status as a Chartered Manager (Chartered Management Institute) in combination with IBM Academic Initiative membership, enhances my professional ability to create contemporary learning experience.
My research interests are generally in the domain of Artificial Intelligence for research and business. I have used extensively multi-disciplinary analytical methods (Decision trees, Neural and Bayesian networks) to develop innovative socio-economic profiling of business tax evaders with implications for public policy (my PhD). I have special interest in:
- Cognitive computing, Deep learning and Reasoning
- Automated Knowledge Acquisition and Predictive Analytics