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Prashant Rajaram is an Assistant Professor at Ivey Business School, specializing in marketing. He earned his PhD from the Ross School of Business at the University of Michigan. His research focuses on understanding and documenting experiential consumption of digital products and media, as well as implementing causal and interpretable machine learning methods for behavioral data analysis. His projects include developing a novel two-step interpretation approach grounded in deep learning theory, which identifies new associations between influencer video features on YouTube and measures of shallow and deep engagement. Additionally, he studies the effects of different ad delivery strategies on ad avoidance and content avoidance behavior on platforms like Hulu, revealing contrasting effects of these levers and providing insights for designing ad delivery tailored to platform goals.
Streams include Archaeology and Bioarchaeology, and Sociocultural Anthropology.