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.