Dr. Kalinda Ukanwa uses quantitative and computational modeling methods in her research on responsible artificial intelligence, marketplace disparities, and consumer reputations, especially on bias and fairness in algorithmic decision-making, marketplace disparities, and the impact of consumer reputations on firms.

Her research is published in top journals including the Proceedings of the National Academy of Sciences and the American Journal of Sociology, as well as chapters within edited books. She serves as a reviewer for several academic journals, including the Journal of Marketing, Journal of Marketing Research, Marketing Science, Journal of Consumer Research, Proceedings of the National Academy of Sciences, and Journal of Interactive Marketing. Dr. Ukanwa has presented her research to companies including Twitter Inc., RAND Corp, and Publicis Group. She has also presented her research at various institutions such as Harvard, Yale, Wharton, Duke, the Oxford Centre for Corporate Reputation, and University of Southern California. She is a two-time AMA-Sheth Fellow, the winner of the 2018 Eli Jones Promising Young Scholar Award, a finalist for the 2018 INFORMS Service Science Best Student Paper Award, 2019 Howard/AMA Doctoral Dissertation Award, and the 2020 AMS Mary Kay Doctoral Dissertation Award.

Professor Ukanwa holds three degrees from Stanford University: a B.S. and M.S. in Industrial Engineering and an MBA. She obtained her PhD in Business Administration (Quantitative Marketing) from the University of Maryland at College Park. In a prior life, Professor Ukanwa was an industrial engineer, financial analyst, and finance/business analytics executive at Walt Disney, Citigroup, Viacom, and Kaplan.