Skip to main content

Remi Daviet

Remi Daviet
Assistant Professor | Marketing
608-262-2224
4184 Grainger Hall

Biography

Remi Daviet joined the Wisconsin School of Business in June 2021 as an Assistant Professor in the Marketing Department.

In a first stream of research, professor Daviet works on extracting valuable insight from multiple sources of data with the help of Machine Learning and AI. This also leads to the development of methods to optimize and automate business processes. Applications are diverse, such as automating ad design, optimizing packaging and product pictures, selecting human models for ad campaigns, analysing communities of social media influencers, and improving room presentations for hotels.

In a second stream of research, he focuses on understanding and predicting consumer decisions by combining quantitative modeling with advanced statistics. His models of decision-making rely on insights from many fields: Neuroscience, Cognitive Science, Psychology, Genomics, and Economics.

Before joining the Wisconsin School of Business, Professor Daviet was a Post-Doctoral Researcher in Marketing at The Wharton School, University of Pennsylvania. He completed his PhD in Economics at the University of Toronto, specializing in Bayesian econometrics and decision modeling.

Research

Selected Accepted Journal Articles

Daviet, R. & Nave, G. The Value of Genetic Data in Predicting Preferences: A Study of Food Taste Journal of Marketing Research

Selected Published Journal Articles

Daviet, R. & Webb, R. (2023). A test of attribute normalization via a double decoy effect Journal of Mathematical Psychology

Burda, M. & Daviet, R. (2023). Hamiltonian Sequential Monte Carlo with Application to Consumer Choice Behavior Econometric Reviews

Daviet, R. & Aydogan, G. & Jagannathan, K. & Spilka, N. & Koellinger, P. & Kranzler, H. & Nave, G. & Wetherill, R. (2022). Associations between alcohol consumption and gray and white matter volumes in the UK Biobank Nature Communications

Daviet, R. & Nave, G. & Wind, Y. (2022). Genetic Data: Potential Uses and Misuses in Marketing Journal of Marketing

Aydogan, G. & Daviet, R. & Linner, R. & Hare, T. & Kable, J. & Kranzler, H. & Wetherill, R. & Ruff, C. & Koellinger, P. & Nave, G. (2021). Genetic underpinnings of risky behaviour relate to altered neuroanatomy Nature Human Behaviour

Nave, G. & Daviet, R. & Nadler, A. & Zava, D. & Camerer, C. (2020). Reflecting on the Evidence: A Reply to Knight, McShane, et al. (2020) Psychological Science

Presentations

Waseda University Seminar (2023) Bayesian Deep Learning Deep Learning for Small or Imbalanced Datasets

Goethe University Frankfurt Seminar (2023)

Vrije Universiteit Amsterdam Seminar (2023)

AMA Summer 2022 (2022) Leveraging the Social Network Structure of Influencers to Understand and Predict User Engagement

Grenoble EM Seminar (2022)

Theory and Practice in Marketing (2022) Age is More Than Just a Number: Biological Age and Its Value to Consumer Research