Refereed Journals

    * First Author and Authors listed Alphabetically
  • Fulfillment By Platform: Antitrust and Upstream Market Power with J. Zhang, and S. Veeraraghavan
    • Forthcoming at Operations Research
    • In Proceedings of ACM Conference on Economics and Computation (EC '21)
    • Honorable Mention, Best Student Paper Award, College of Supply Chain Management 2021
    • Finalist, Best Student Paper Award, INFORMS Service Science 2021
    • Selected for WISE 2018
  • Vertical Integration and Market Power in Supply Networks with K. Arora and M. Sahare
    • Forthcoming at Manufacturing & Service Operations Management
    • Selected for IFORM SIG 2025
  • Frontiers: Can LLMs Capture Human Preferences? with Ali Goli
    • Marketing Science, 2024
  • When to be Agile: Ratings and Version Updates in the Mobile App Market* with G. Allon, G. Askalidis, R. Berry, N. Immorlica, and K. Moon
    • Management Science, 2021
    • 1st place, Best Student Paper Award, POMS Product Innovation and Technology 2020
    • Selected for MSOM Supply Chain SIG 2019
  • Characterization of the Toll of Caring for COVID-19 on ICU Nursing Staff with K. Laudanski, K. Moon, Y. Chen, and M. Restrepo
    • Critical Care Explorations, 2021

Working Papers

  • Choice Models and Permutation Invariance: Demand Estimation in Differentiated Products Markets with Ye Liu and Hema Yoganarasimhan
    • Minor Revision at Marketing Science
    • In NeurIPS 2024 Workshop: Causal Representation Learning
  • Machine Learning Instrument Variables for Causal Inference with Kartik Hosanagar and Amit Gandhi
    • Under 3rd round review at Marketing Science
    • In Proceedings of ACM Conference on Economics and Computation (EC '20)
  • Network Externalities and App Store Fees in Mobile Platforms with Kartik Hosanagar and Aviv Nevo
    • Under Review at Operations Research
    • Selected for Marketing Dynamics Conference 2018
    • Selected for WISE 2018
  • Causal Gradient Boosting: Boosted Instrument Variable Regression with Edvard Bakhitov
    • Major Revision at Journal of Machine Learning Research
    • In Proceedings of ACM Conference on Economics and Computation (EC '22)
    • In UAI 2021 Workshop: Advances in Causal Inference
    • In ICML 2021 Workshop: The Neglected Assumptions In Causal Inference
    • In NeurIPS 2021 Workshop on Machine Learning meets Econometrics
  • Causal Bandits: Online Learning in Endogeneous Settings with Jingwen Zhang and Y. Chen
    • Under review at Management Science
    • In NeurIPS 2022 Workshop: Causal ML for Impact
    • Finalist, Best Paper Award, CSWIM 2023
  • Deep Causal Inequalities: Demand Estimation in Differentiated Products Markets with Edvard Bakhitov and Jiding Zhang
    • Preparing for submission at Management Science
    • In KDD 2021 Workshop on Machine Learning for Consumers and Markets, 2021
    • In UAI 2021 Workshop: Advances in Causal Inference
    • In ICML 2021 Workshop: The Neglected Assumptions In Causal Inference
    • In ICML 2021 Workshop: Machine Learning for Data: Automated Creation, Privacy, Bias
    • In NeurIPS 2021 Workshop on Machine Learning meets Econometrics
  • Causal Regressions for Unstructured Data with Bolong Zheng
    • In NeurIPS 2024 Workshop: Causal Representation Learning

Work in Progress

  • Deep Inverse Demand Estimation in Differentiated Products Markets with Jing Tao

Refereed Conference Proceedings

  • Causal Regressions for Unstructured Data with Bolong Zheng
    • NeurIPS 2023 Workshop on Causal Representation Learning
  • Choice Models and Permutation Invariance with Ye Liu and Hema Yoganarasimhan
    • NeurIPS 2023 Workshop on Causal Representation Learning
  • Causal Gradient Boosting: Boosted Instrument Variable Regression with Edvard Bakhitov
    • ACM Conference on Economics and Computation (EC '22)
  • Causal Bandits: Online Learning in Endogeneous Settings with Jingwen Zhang and Yifang Chen
    • NeurIPS 2022 Workshop: Causal ML for Impact
  • Fulfillment By Platform: Antitrust and Upstream Market Power with J. Zhang and S. Veeraraghavan
    • ACM Conference on Economics and Computation (EC '21)
  • Deep Causal Inequalities: Demand Estimation in Differentiated Products Markets with Edvard Bakhitov and Jiding Zhang
    • NeurIPS 2021 Workshop on Machine Learning meets Econometrics
  • Machine Learning Instrument Variables for Causal Inference with Amit Gandhi and Kartik Hosanagar
    • ACM Conference on Economics and Computation (EC '20)
  • Deploying PAWS to combat poaching: game-theoretic patrolling in areas with complex terrain with F. Fang, H. Nguyen, R. Pickles, Y. Lam, R. Clements, Bo An, M. Tambe
    • Thirtieth AAAI Conference on Artificial Intelligence, 2016
  • PAWS-A Deployed Game-Theoretic Application to Combat Poaching with F. Fang, H. Nguyen, R. Pickles, Y. Lam, R. Clements, Bo An, C. Schwedock, M. Tambe, A. Lemieux
    • AI Magazine, 2017
  • Deploying PAWS: Field optimization of the protection assistant for wildlife security with F. Fang, H. Nguyen, R. Pickles, Y. Lam, R. Clements, Bo An, C. Schwedock, M. Tambe, A. Lemieux
    • Twenty-Eighth IAAI Conference, 2016
    • Winner of Innovative Application Award
  • Protecting the NECTAR of the Ganga River through game-theoretic factory inspections with B. Ford, M. purple, A. Yadav, A. Sinha, B. Srivastava, C. Kiekintveld, M. Tambe
    • International Conference on Practical Applications of Agents and Multi-Agent Systems, 2016

Book Chapters

  • Artificial Intelligence and Conservation. Artificial Intelligence for Social Good. Cambridge: Cambridge University Press, 2019.