Assoc. Prof. Dr Tatiana Gherman

Dr Tatiana Gherman, MBA (1st place, Cum Laude, Valedictorian), PhD, PGCertRDS, is an Associate Professor within the Faculty of Business and Law at the University of Northampton, UK. She obtained her PhD from Loughborough University, UK, who also fully funded her studies. She further has two professional certificates in big data and analytics from MIT Sloan School of Management (USA) and two professional certificates in predictive analytics and machine learning with business applications from the Indian Institute of Management Bangalore (India). She is an Advance HE Certified External Examiner, UK and has a Postgraduate Certificate in Research Degree Supervision. She is a 2023 Women in Data Science (WiDS) Ambassador (in collaboration with WiDS Stanford, USA).

She has more than a decade of teaching and research experience. Proven track record of delivering written research reports and articles, as well as research paper presentations at international conferences. She has published various research outputs in high-impact journals, including the Journal of the Operational Research Society, Annals of Operations Research, and Expert Systems with Applications. She is a recipient of various academic honours and awards, among which the 2022 Diamond Research Award and the 2019 GDN INFORMS/Springer Researcher Award. She is also a Beta Gamma Sigma "Best in Business" awardee.

Overall, with knowledge of and practical experience in the application of a variety of qualitative and quantitative research methods. Currently researching how Machine Learning and Artificial Intelligence tools can support various business functions to help make business management practices more effective; with particular interest in how to design Artificial Intelligence techniques grounded in and informed by patterns of social interaction and communication. 

Areas of research interests and fields of expertise include Artificial Intelligence/Machine Learning for SDGs, Data Science, Big Data, and other Advanced Quantitative Analytics (at different levels), including Productivity and Performance Measurement; also, Group Decision Support/Facilitation, Human-Computer Interaction, Workplace Studies, Behavioural Studies, Conversation Analysis, and Ethnomethodology. 

She is an Associate Editor for the journal Machine Learning with Applications.

Currently supervising 4 DBA students and 2 PhD students.

Areas of research interests and fields of expertise include Artificial Intelligence/Machine Learning for SDGs, Data Science, Big Data, and other Advanced Quantitative Analytics (at different levels), including Productivity and Performance Measurement; also, Group Decision Support/Facilitation, Human-Computer Interaction, Workplace Studies, Behavioural Studies, Conversation Analysis, and Ethnomethodology.