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Nikhil Malik studies the economic implications of Machine Learning and disruptive technologies. His recent work touches on Zillow’s machine learning-based pricing of homes and Bitcoin’s pricing and payments. Malik's research highlights issues related to pricing, adoption, and bias fairness. He has received past awards and fellowships from notable institutions, including PNC Bank and Ripple, and has experience designing financial technology at Goldman Sachs. With a strong background in Marketing and FinTech, Nikhil brings expertise to the intersection of these fields. He advocates for transparency in AI applications in housing markets and explores the 'attractiveness premium' in the job market, highlighting how perceived attractiveness impacts salary and career outcomes. Besides teaching, he contributes to discussions in major publications regarding the implications of AI and economic models in finance and marketing.
University of Southern California Marshall School of Business • Los Angeles, CA
Teaching and researching economic implications of Machine Learning and AI in marketing.
Ph.D. programs include specializations in Accounting, Data Sciences and Operations, Finance, Management and Organization, and Marketing.