Working Papers

    * Authors listed Alphabetically

  • Digital Platforms and Online Marketplaces

    • When to be Agile: Reviews and Version Updates in Mobile App Markets * with G. Allon, G. Askalidis, R. Berry, N. Immorlica and K. Moon
      • (paper)
      • Forthcoming at Management Science
      • Won 1st Place Best Student Paper Award 2020 POMS Product Innovation and Technology
    • Network Externalities and Cross-Platform App Development in Mobile Platforms with Kartik Hosanagar and Aviv Nevo
      • (paper)
      • Major Revision at Management Science
    • Fulfillment By Platform: Antitrust and Upstream Market Power with Jiding Zhang, and Senthil Veeraraghavan
      • (paper)
      • Major Revision at Operations Research
      • Honorable Mention, Best Student Paper Competition 2021 POMS College of Supply Chain Management
      • Finalist, Best Student Paper Competition INFORMS Service Science 2021 ( Results not declared yet)
      • In Proceedings of ACM Conference on Economics and Computation (EC ’21)

  • Econometrics and Machine Learning

    • Machine Learning Instrument Variables for Causal Inference with Amit Gandhi and Kartik Hosanagar
      • (paper)
      • In preparation for submission at Marketing Science
      • In Proceedings of ACM Conference on Economics and Computation (EC ’20)
    • Causal Gradient Boosting: Boosted Instrument Variable Regression* with Edvard Bakhitov
      • (paper) (code)
      • Major Revision at Journal of Machine Learning Research
      • In Proceedings of ACM Conference on Economics and Computation (EC ’22)
      • Accepted to the UAI 2021 Workshop: Advances in Causal Inference
      • Accepted to the ICML 2021 Workshop: The Neglected Assumptions In Causal Inference
      • Accepted to the NeurIPS 2021 Workshop on Machine Learning meets Econometrics
    • Deep Causal Inequalities: Demand Estimation in Differentiated Products Markets* with E. Bakhitov and J. Zhang
      • In preparation for submission at Marketing Science
      • Accepted to the KDD 2021 Workshop: Machine Learning for Consumers and Markets
      • Accepted to the UAI 2021 Workshop: Advances in Causal Inference
      • Accepted to the ICML 2021 Workshop: Machine Learning for Data: Automated Creation, Privacy, Bias
      • Accepted to the ICML 2021 Workshop: The Neglected Assumptions In Causal Inference
      • Accepted to the NeurIPS 2021 Workshop on Machine Learning meets Econometrics
    • Causal Bandits: Online Learning in Endogeneous Settings with Jingwen Zhang and Y. Chen
      • (paper)
      • Major Revision at Marketing Science
      • Accepted to the NeurIPS 2022 Workshop: Causal ML for Impact
      • Accepted to the NeurIPS 2022 Workshop: Causality-dynamical systems
    • Choice Models and Permutation Invariance with Ye Liu and Hema Yoganarasimhan
      • (paper)

Work in Progress

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

Refereed Conference Proceedings

  • Causal Gradient Boosting: Boosted Instrument Variable Regression* with Edvard Bakhitov
    • ACM Conference on Economics and Computation (EC ’22)
  • Fulfillment By Platform: Antitrust and Upstream Market Power with Jiding Zhang, and Senthil Veeraraghavan
    • ACM Conference on Economics and Computation (EC ’21)
  • Machine Learning Instrument Variables for Causal Inference with Amit Gandhi and Kartik Hosanagar
    • ACM Conference on Economics and Computation (EC ’20)
  • Deploying PAWS: Field Optimization of the Protection Assistant for Wildlife Security with Fei Fang, Thanh H. Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, Milind Tambe, and Andrew Lemieux
    • AAAI-16
    • Winner of Innovative Application Award
  • PAWS—A deployed game-theoretic application to combat poaching with Fei Fang, Thanh H. Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, Milind Tambe, and Andrew Lemieux
    • AI Magazine 2016
  • Protecting the NECTAR of the Ganga River through Game-Theoretic Factory Inspections with Benjamin Ford, Matthew Brown, Amulya Yadav, Arunesh Sinha, Biplav Srivastava, Christopher Kiekintveld and Milind Tambe
    • PAAMS-16: Proc. 14th 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.