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Ashish Kumar Jha


Ashish Kumar Jha is an Associate Professor in the field of Business Analytics at Trinity Business School, Trinity College Dublin. He is the founding director of M.Sc. Business Analytics (Ranked 1st in Ireland and 24th Globally). He is a co-director of Trinity Centre for Digital Business and Analytics. He is a funded Investigator at SFI Research Centre ADAPT.

He is a member of EU Cost Action on Fintech and AI. Ashish holds a PhD in Information Systems and his research revolves around the areas of fake news and social media analysis. He uses statistical and text mining and econometric techniques to understand how firms and consumers interact on social platforms and its effects for both firms and their consumers.

He is a distinguished member of Association of Information Systems and is a committee member for AIS early career awards. His papers have been published in many top journals of the field including Journal of MIS (listed in FT list of preferred journals), Information and Management, International Journal of Production Economics, Communications of AIS among others.

He serves as an Associate Editor for Information & Management and Information Systems Frontiers and also serves as ad-hoc reviewer and associate editor for various conferences and journals including International Conference on Information Systems, European Conference on Information Systems, European Journal of Information Systems, Decision Support Systems, Expert System with Applications, Decision Sciences, International Journal of Production Economics etc. Ashish has been a part of research groups working on robotic process automation in IT services industry and jointly holds multiple patents in the field of IT services management and optimization. He has also worked closely with businesses and advised them as well as written teaching cases on firms like Microsoft, Bosch, Wipro etc.

He is looking to supervise projects that revolve around the problem of identifying the business value of data and the risk associated with misinformation in unearthing. This would use text mining and other statistical techniques and business theory to create an explainable AI tool/framework to identify the possible human causes for misinformation and the risk, in-terms of market value etc. for the loss of data. He is open to broad research in field of corporate misinformation and its value in social media spaces.

Research Areas:

Explainable AI, Value of Data, Misinformation; social media