In my research, I combine traditionally strongly conceptual and theoretical approaches to information systems research with quantitative, data-informed and computational tools with the aim to foster methodological techniques allowing new insights for management research and practice. I'm committed to multidisciplinary teaching and keen to explore developing competencies needed for managers to work with data and analytics. I have taught data, technology and e-business subjects at a number of institutions, including London School of Economics and Political Science and University College London. Both my research and teaching benefit from past industry experience as an entrepreneur in e-learning, IT and communication. Learn more about my research below.
I research the managerial side of data science in organizations. Developing robust theories of managing data science is required for this function to work effectively in organizations, and to ensure that a higher number of data science initiatives and projects achieve the expected success, realizing the promised benefits for organizations that invest in their development. I combine qualitative and computational approaches to advance research in this area.
I’m interested in how data is used in Artificial Intelligence systems in organizations, and how this changes what it means to know. I approach this subject both from an AI perspective and a philosophical angle focusing on epistemology. Through my research in this area, I want to help organizations think better with AI. You can learn more about my research here.
I design online courses and develop digital pedagogies.
Before joining academia, I spent six years running my own businesses in the fields of communication and e-learning. I became increasingly drawn to research, learning, and teaching with information technologies. If you want to know more, connect on LinkedIn.