Research

Publications

Artem Timoshenko and John R. Hauser (2018), “Identifying Customer Needs from User-Generated Content,” Accepted, Marketing Science [PDF]

  • Job Market Paper
  • Winner, 2017 MSI Alden G. Clayton Doctoral Dissertation Proposal Award
  • Winner, 2016 ISMS Doctoral Dissertation Proposal Award 

Working Papers

Duncan Simester, Artem Timoshenko, and Spyros I. Zoumpoulis (2018), “Targeting Prospective Customers: Robustness of Machine Learning Methods to Typical Data Challenges,” Minor Revision, Management Science [PDF]

Duncan Simester, Artem Timoshenko, and Spyros I. Zoumpoulis (2017), “Efficiently Evaluating Targeting Policies Using Field Experiments,” Major Revision, Management Science

Theodoros Evgeniou, Duncan Simester, Artem Timoshenko, and Spyros I. Zoumpoulis (2017), “Using Past Responders to Target Non-Responders” 

Work In Progress

“Cross-Category Product Choice: A Scalable Deep-Learning Approach,” with Sebastian Gabel

“Deep Learning to Predict Consumer Aesthetic Preferences and Augment Product Designers,” with Alex Burnap and John R. Hauser

“Leveraging Incomplete Customer Journeys with Deep Neural Models,” with Paramveer Dhillon and Glen Urban

“Optimal Product Design with Deep Learned Visual Features,” with Liu Liu

“Discrete Choice Modeling with Deep Neural Networks”

Papers in Proceedings

Artem Timoshenko and John R. Hauser (2016), “Mining and Organizing User-Generated Content to Identify Attributes and Attribute Levels,” Proceedings of the Sawtooth Software Conference, Park City, Utah, September 28-30, 2016