B.Sc. Economics and Business Economics, Maastricht University;
MRes in Business (Quantitative Marketing), Tilburg University
During her undergraduate studies, Roshini worked as a research assistant at the Yale School of Management on a project using AI to detect persuasion success by analysing multimodal video data to engineer behavioural indicators from gestures, vocal dynamics, and speech. This experience sparked her interest in how unstructured data can be used to derive theory-driven constructs and drew her toward quantitative marketing research. She went on to pursue a Research Master in Quantitative Marketing at Tilburg University, and has since remained at Tilburg as a predoctoral researcher and Junior Lecturer. Her primary research project examines how Question & Answer widgets on platforms influence consumer ratings in subjective product settings such as books, combining causal inference and text-as-data methods. She has presented this work at WISE, DigiEcon, and AMA Winter. As a Junior Lecturer, she teaches R programming, online data collection, causal inference, and digital marketing across Tilburg's M.Sc. Marketing Analytics and B.Sc. International Business programmes, and supervises bachelor's and master's theses. Her current research interests centre on how digital platforms and AI-mediated information environments shape consumer search behaviour and decision-making.
