An updated version can be found here

Research interests

I focus on understanding and predicting decisions using quantitative modeling and advanced statistics / machine learning. My models of decision-making rely on insights from many fields: Neuroscience, Cognitive and Mathematical Psychology, Genomics, Economics and Computer Science.

  • Econometrics / Machine Learning
    • Neural Networks
    • Bayesian Methods and Computational Statistics
    • Big Data and High Performance Computing (HPC)
  • Quantitative Marketing
    • Demand analysis
    • Quantitative Behavioral Modelization and Decision Processes
    • Consumer Neuroscience and Consumer Genomics
  • Behavioral Neuro-Genomics

Work in Progress

MKTG Marketing
MTHD Method / Statistics
NEUR Consumer Neuroscience & Neuro-Genomics
MKTG "Bayesian Deep Learning for Small Datasets: Predicting Sales from Bottle Design",
Remi Daviet
MKTG "Foundations of the Decoy Effect: Putting Theory to the Test",
Ulrich Bergmann, Remi Daviet, Ernst Fehr
MKTG "Beliefs updating and value perception of products",
Remi Daviet, Lin Fei.

Papers and publications

Published & Revision Invited

NEUR "Reflecting on the Evidence: A Reply to Knight, McShane, et al. (2020)",
Gideon Nave*, Remi Daviet*, Amos Nadler, David Zava, Colin Camerer (* for equal contribution)
Psychological Science (article, supplement)
MKTG "The Consumer DNA Revolution: Why Marketers Should Care About Genomic Data",
Remi Daviet, Gideon Nave, Yoram Wind
R&R (Journal of Marketing), draft available on demand.
MKTG "Hamiltonian Sequential Monte-Carlo: Application to Consumer Demand",
Martin Burda, Remi Daviet
R&R (Econometric Reviews), Latest version

NEUR "Genetic underpinnings of risky behavior relate to altered neuroanatomy",
Gökhan Aydogan, Remi Daviet, Gideon Nave, Philipp Koellinger et Al.
R&R (Nature Human Behaviour), Latest version, Pre-registered with the Open Science Framework
NEUR "Multimodal brain imaging study of 19,825 participants reveals adverse effects of moderate drinking",
Remi Daviet, Gideon Nave, Philipp Koellinger, Reagan Wetherill et Al.
R&R (Nature Communications), Latest version, Pre-registered with the Open Science Framework
MKTG "Social Preference Estimation Using Adaptive Experimental Design",
Taisuke Imai, Devdeepta Bose, Remi Daviet, Gidi Nave, Colin Camerer
R&R (Experimental Econ.), Submitted for pre-results review.

Under Review

MKTG "A Double Decoy Experiment to Distinguish Theories of Dominance",
Remi Daviet, Ryan Webb

Working Papers

MKTG "Neural Attribute Normalization: An Application to Product Portfolio Optimization",
Remi Daviet
Latest version
MTHD "Sequential Optimal Inference for Experiments with Bayesian Particle Filters",
Remi Daviet
Reject & Resubmit (JMR), Latest version
MTHD "Sequential Monte Carlo for Hierarchical Bayes with Large Datasets",
Remi Daviet
Latest version
MTHD "Multialternative Drift Diffusion Model: Estimation with Hit and Run Particles",
Remi Daviet
Draft available on demand.
MTHD "Inference with Hamiltonian Sequential Monte Carlo Simulators",
Remi Daviet
Arxiv, Latest version , C++/CUDA code


"Methods for statistical analysis and prediction of discrete choices"
Published version

  • Chapter 1: Attribute Divisive Normalization : A Neural Decision Model for Discrete Choice
  • Chapter 2: Hamiltonian Sequential Monte Carlo with Application to Consumer Choice Behavior
  • Chapter 3: Sequential Optimal Inference for Experiments with Sequential Monte Carlo Methods