Julian Runge is a behavioral economist and digital marketing researcher. He obtained a B.Sc. in Economics at Goethe University Frankfurt a.M and the New School for Social Research (as a Fulbright Scholar) and an M.Sc. and Ph.D. in Economics and Management Science at Humboldt University Berlin. During his doctoral studies, Julian was a repeat visiting researcher at Stanford University, and, as a postdoc, he worked as an academic researcher in Facebook’s marketing science R&D group. Before joining Northeastern University, he was a visiting scholar at Duke University with a postdoctoral fellowship from RWTH Aachen University. In addition to his research pursuits, Julian advises companies on strategically using data, science, and algorithms to fuel their growth and customer experiences.


  • PhD Economics and Management Science, Humboldt University Berlin
  • MSc Economics and Management Science, Humboldt University Berlin
  • BSc Economics, Goethe University Frankfurt a.M.
  • MA Economics (non-degree, Fulbright Scholarship), The New School for Social Research

Selected Publications

  • Algorithmic Assortative Matching on a Digital Social Medium, with Kristian Lopez Vargas and Ruizhi Zhang (2022, Information Systems Research, forthcoming).
  • Price Promotions and “Freemium” App Monetization, with Jonathan Levav and Harikesh Nair (2022, Quantitative Marketing and Economics, forthcoming.
  • Privacy-Centric Digital Advertising: Implications for Research, with Garrett Johnson and Eric Seufert (2022, Customer Needs and Solutions, forthcoming).
  • “Dark Patterns” in Online Services: A Motivating Study and Agenda for Future Research, with Daniel Wentzel, Ji Young Huh and Allison Chaney (2022, Marketing Letters, forthcoming).
  • The Role of Randomized Control Trials in Online Demand Generation: Exploratory Evidence from Facebook, with Harikesh Nair (2021, International Conference on Information Systems (ICIS)).
  • Experimentation and Performance in Advertising: An Observational Survey of Firm Practices on Facebook, with Steven Geinitz and Simon Ejdemyr (2020, Expert Systems w. Applications).
  • Customer Lifetime Value Prediction in Non-Contractual Freemium Settings: Chasing High-value Users Using Deep Neural Networks and SMOTE, with Rafet Sifa, Christian Bauckhage and Daniel Klapper (2018, Proceedings of the 51st Hawaii Intern. Conf. on System Sciences.
  • Predicting Purchase Decisions in Mobile Free-to-play Games, with Rafet Sifa, Fabian Hadiji, Anders Drachen, Kristian Kersting and Christian Bauckhage (Proceedings of the 11th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment).
  • Churn Prediction for High-value Players in Casual Social Games, with Peter Gao, Florent Garcin and Boi Faltings (2014, Proceedings of the 2014 IEEE Conference on Computational Intelligence and Games).

Awards and Recognition

  • Best Paper Award, AAAI Conference on Artificial Intelligence in Interactive Digital Entertainment (AIIDE)
  • Runner-up Best Paper Award, IEEE Conference on Computational Intelligence in Games (CIG)
  • Fulbright Scholarship, study abroad at the New School for Social Research
  • Scholarship from the Economic Society of Humboldt University Berlin
  • Scholarship from Friedrich-Ebert-Foundation

Selected Presentations

  • Marketing Science Research at Facebook
  • University College Dublin, virtual seminar, 2021
  • Duke University, virtual seminar, 2020
  • Price Personalization in Freemium Settings
  • 2020 Conference on Artificial Intelligence, Machine Learning, and Business Analytics, NYU Stern/CMU/Temple, Online
  • Theory and Practice of Marketing Conference 2019, Columbia University, NYC, NY
  • INFORMS Revenue Management and Pricing Conference 2019, Stanford Univ., CA
  • INFORMS Marketing Science Conference 2017, Univ. of Southern California, Los Angeles, CA
  • Stitch Fix Algorithm Hour, 2019, San Francisco, CA
  • Uber Behavioral Science Symposium 2019, San Francisco, CA
  • Customer Lifetime Value Prediction in Non-Contractual Freemium Settings
  • Hawaii International Conference on Systems Sciences (HICSS), 2018, Hawaii
  • Interactive Marketing Research Conference 2018, Amsterdam, Netherlands
  • Freemium Pricing: Evidence from a Large-scale Field Experiment
  • MIT Conference on Digital Experimentation (CODE) 2016, Boston, MA