Research Interests

• Automated decision making
• Statistical inference for treatment assignment policies
• Causal inference
• Interpretable machine learning

Academic Qualification

• PhD 2021 New York University, Information Systems
• MBA 2015 INCAE Business School
• B.Sc. 2011 Instituto Tecnológico de Costa Rica, Computer Science

Academic And Professional Experience

• Assistant Professor, The Hong Kong University of Science and Technology, 2021-present

SELECTED PUBLICATIONS

• Fernández-Loría, C., Cohen, M., and Ghose, A. “Evolution of Referrals Over Customers' Life Cycle: Evidence from a Ride-Sharing Platform.” Information Systems Research (2022).
• Fernández-Loría, C., Provost, F., Anderton, J., Carterette, B., and Chandar, P. “A Comparison of Methods for Treatment Assignment with an Application to Playlist Generation.” Information Systems Research (2022).
• Fernández-Loría, C., and Provost, F. “Causal Decision Making and Causal Effect Estimation Are Not The Same... and Why It Matters.” INFORMS Journal on Data Science (2022).
• Fernández-Loría, C., Provost F., and Han, X. “Explaining data-driven Decisions Made by AI Systems: The Counterfactual Approach.” MIS Quarterly (2022).
• Fernández-Loría, C., and Provost, F. “Causal Classification: Treatment Effect Estimation vs. Outcome Prediction.” Journal of Machine Learning Research (2022).