Remi Daviet

Assistant Professor of Marketing, University of Wisconsin-Madison

Curriculum Vitae

Last update: 2026-04-02

Research Interests

Using Artificial Intelligence (AI) for Insight, Decisions, and Automation
  • Methodology: Machine Learning / AI, Bayesian Statistics, Quantitative Modeling
  • Applications: Advertising, analysis and generation of unstructured data (images and language)
Understanding Consumer Biology
  • Methodology: Consumer physiology, consumer neuroscience, consumer genomics
  • Applications: Consumer aging, using biological data to understand the marketplace, understanding the antecedents and effects of consumption

Academic Positions

Associate Professor of Marketing (non-tenured) | Starting 2026
INSEAD
Assistant Professor of Marketing | 2021 - 2026
Wisconsin School of Business, University of Wisconsin-Madison
Post-Doctoral Researcher | 2018 – 2021
Wharton Marketing Department, University of Pennsylvania
Supervision: Gideon Nave & Eric Bradlow

Education

Ph.D. Economics | University of Toronto | 2014 - 2018
  • Dissertation: Methods for Statistical Analysis and Prediction of Choice
  • Honors: Distinction in Econometrics
  • Major: Econometrics / Minor: Industrial Organization
M.Sc. Economics | University of Montreal
M.B.A. | Laval University
B.Sc. Management | University of Lausanne (HEC)

Other Professional Experience

IT & Digital Marketing Consulting (Founder)
Daviet Innovation Inc. | 2011 - 2014

Academic Papers

(* equal contribution)

Accepted & Published

  1. Leveraging Generative AI to Create Visual Content in Digital Advertising
    Remi Daviet*, Yohei Nishimura*
    Marketing Science (Forthcoming) (2026)
  2. Digital Platforms 2.0: Emerging Topics, Opportunities, and Challenges
    S. Banerjee, I. Chakraborthy, H. Choi, H. Datta, R. Daviet, C. Farronato, M. Kim, A. Lambrecht, P. Machanda, A. Oery, A. Sen, M. Van Alstyne, P. Vana, K.C. Wilbur, X. Zhang, B. Zhou
    International Journal of Research in Marketing (2026)
  3. The Value of Genetic Data in Predicting Preferences: A Study of Food Taste
    Remi Daviet*, Gideon Nave*
    Journal of Marketing Research (2024)
  4. Hamiltonian Sequential Monte Carlo with Application to Consumer Choice Behavior
    Martin Burda*, Remi Daviet*
    Econometric Reviews (2023)
  5. A Test of Competing Theories of Attribute Normalization via a Double Decoy Effect
    Remi Daviet*, Ryan Webb*
    Journal of Mathematical Psychology (2023)
  6. Associations between alcohol consumption and gray and white matter volumes in the UK Biobank
    Remi Daviet*, Gideon Nave*, Philipp Koellinger, Reagan Wetherill et Al.
    Nature Communications (2022)
  7. Genetic Data: Potential Uses and Misuses in Marketing
    Remi Daviet*, Gideon Nave*, Yoram Wind
    Journal of Marketing (2022)
  8. Genetic Underpinnings of Risky Behavior Relate to Altered Neuroanatomy
    Gökhan Aydogan, Remi Daviet, Gideon Nave, Philipp Koellinger et Al.
    Nature Human Behaviour (2021)
  9. Reflecting on the Evidence: A Reply to Knight, McShane, et al. (2020)
    Gideon Nave*, Remi Daviet*, Amos Nadler, David Zava, Colin Camerer
    Psychological Science (2020)

Under Review & Revision Invited

  1. Biological Age and its Value to Marketing Theory and Practice
    Steven Shaw, Remi Daviet, Gideon Nave
    Under Review (Round 3) at the Journal of Marketing (2024)
  2. Creating Effective Digital Ads: Automatic Bayesian Combinatorial Design
    Remi Daviet*, Connor Campbell*, Neil Morgan
    R&R (Round 1) at the Journal of Marketing Research (2024)

Working Papers

  1. Managing Innovation Risk in Package Design with Bayesian AI-Assisted Creation
    Remi Daviet, Jungeun Lim
    Working Paper (2024)
  2. Reference Points in Multi-Attribute Value Normalization
    Remi Daviet
    Working Paper (2024)
  3. Leveraging the Social Network Structure of Influencers to Understand and Predict User Engagement
    Pankhuri Malhorta*, Remi Daviet*
    Working Paper (2022)
  4. Multialternative Drift Diffusion Model: Estimation with Path Splitting
    Remi Daviet
    Draft available on demand. (2020)
  5. Sequential Optimal Inference for Experiments with Bayesian Particle Filters
    Remi Daviet
    Working Paper (2019)
  6. Inference with Hamiltonian Sequential Monte Carlo Simulators
    Remi Daviet
    Arxiv (2018)

Work in Progress

  1. Content-Aligned Cover Design: A Multimodal Deep Learning Approach to Understanding and Enhancing Media Cover Success
    Yijing Xu*, Remi Daviet*, Maria Hademer
  2. A Recommendation System with Hierarchical Bayes for Large Datasets
    Remi Daviet*, Shervin Shahrokhi Tehrani*, Sharon Shahrokhi Tehrani
  3. Deconstructing the Roles of Brand, Design, and Consistency in Consumer Choice with Generative AI
    Jungeun Lim*, Remi Daviet*, Tanishka Jain
  4. The Design of Sustainable Choices: Integrating Deep Learning, Behavioral Insights, and Structural Analysis
    Jungeun Lim*, Remi Daviet*, Tanishka Jain
  5. AI-driven Interpretable Visual Features for Demand Neuroforecasting
    Brenden Eum, Remi Daviet, Shabnam Hakimi, Brian Knutson, Ryan Webb

Book Chapters

  1. Book Chapter: Uses and Misuses of Genetic Data in Precision Retail
    Remi Daviet*, Gideon Nave*
    Precision Retailing (2023), L. Dube, N. Yang, M. Cohen, B. Monla, University of Toronto Press (2023)

Conference Presentations

  • 2026Choice Symposium (Session Participant)
  • 2024ICAMA Osaka, ISMS Marketing Science
  • 2023Association for Consumer Research, Choice Symposium (Session Organiser)
  • 2022Theory & Practice in Marketing
  • 2021EMAC
  • 2020ISMS Marketing Science, Society for Consumer Psychology (SCP), UT Dallas Bass-FORMS
  • 2019Sloan-Nomis Workshop on Attention and Choice, ISMS Marketing Science, Cognitive Foundations of Economic Behavior (NYU Stern)

Invited Seminars

  • 2026Waseda University
  • 2025Ohio State University, INSEAD, TU Munich (GenAI Lab), University of Alberta (Economics), Yale University
  • 2024Goethe University Frankfurt
  • 2023Waseda University, Northwestern University - Kellogg, Vrije Universiteit Amsterdam, Goethe University Frankfurt
  • 2022Grenoble EM, Journal of Marketing Webinar
  • 2021University of Hong Kong
  • 2020UW-Madison, Rice University, UC Davis, Caltech Camerer Lab, Stanford

Teaching

Courses

  • Bayesian Machine Learning for Marketing (UW-Madison, Graduate)
  • Business Analytics II (UW-Madison, Undergraduate)
  • Experiments for Business Decision Making (Wharton MBA)
  • Empirical Industrial Organization (Toronto)
Award: Teaching Excellence Award (University of Toronto, 2015)

Student Supervision

  • Current PhD Students: Yohei Nishimura, Jungeun Lim
  • Committee Member:
  • Zitian Adam, University of Lausanne (2024)
  • Maysam Ardehali, University of Wisconsin-Milwaukee (2023)
  • Master Students: UW-Madison, Wharton

Service

Reviewing

  • Marketing / Management: Journal of Marketing Research, Marketing Science, Journal of Marketing, Journal of Consumer Research, Management Science, Quantitative Marketing and Economics, International Journal of Research in Marketing, MIS Quarterly.
  • Economics / Econometrics: Journal of Econometrics, Journal of Applied Econometrics, Journal of Applied Economics.
  • Other: Journal of Cognitive Psychology, Behavior Research Methods, Frontiers in Psychology, PNAS Nexus, NPJ Ageing (Nature Group), AI Magazine

Organization

  • Symposium on AI in Marketing (Co-chair, 2024-2026)
  • UW-Madison Marketing Seminars (2023-2026)

Computer Skills

  • Languages: Python, R, MATLAB, C/C++, CUDA, PHP
  • Methods: GPU/Parallel Computing, HPC
  • Environment: Linux, Windows

Other Skills

  • Languages: English (Fluent), French (Fluent), Japanese (Intermediate), German (Intermediate), Korean (Beginner), Chinese (Beginner)
  • Music: Bass, Piano, Drums, Computer-Assisted Composition