Stream 1:  Human-AI Collaboration, AI Policy, AI Applications & AI Methods

Wen Wang, Siqi Pei, and Tianshu Sun (2023) "Unraveling Generative AI from A Human Intelligence Perspective: A Battery of Experiments",  Major Revision, Information Systems Research

Bowen Lou, Hongshen Sun and Tianshu Sun, "GPTs and Labor Markets in the Developing Economy: AI, Geography and Policy", Under Review

Wen Wang, Zhenyue Zhao, and Tianshu Sun (2024) "GPT-doctor: Customizing Large Language Models for Medical Consultation", Under Review

Wen Wang, Mochen Yang, and Tianshu Sun (2024) "Human-AI Co-Creation in Product Ideation: the Dual View of Quality and Diversity",  Under Review

Yicheng Song and Tianshu Sun, Consumer Search and Dynamic Preference: A Deep Structural Econometric Model, Major Revision, Management Science

-- Best Conference Paper Finalist, CIST 2023

Yicheng Song and Tianshu Sun (2023) “Ensembling Experiments to Optimize Customer Journey: A Reinforcement Learning Approach” (Adobe Faculty Research Award 2020, Marketing Science Institute (MSI) Research Grant 2021, CIST 2021),  Forthcoming, Management Science

Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun (2021) “A Prescriptive Analytics Framework for Optimal Policy Deployment using Heterogeneous Treatment Effects”, MIS Quarterly, 45(4), 1807-1832 

Mingxuan Yue, Tianshu Sun, Fan Wu, Lixia Wu, Yinghui Xu and Cyrus Shahabi (2020) “Learning Contextual and Topological Representations of Areas-of-Interest for On-Demand Delivery Application”, Proceedings of the 2020 European Conference on Machine Learning 

Mengxia Zhang, Tianshu Sun, Lan Luo and Joe Golden (2020) “Consumer and AI Co-creation: When and Why can human Improve AI Creation?”, Under Review

Matteo Sesia and Tianshu Sun, "Individualized Conditional Independence Testing under Model-X with Heterogeneous Samples and Interactions",  Under Review

James Enouen, Tianshu Sun and Yan Liu, "Measuring, Interpreting, and Correcting Algorithm Unfairness using Randomized Experiments", Working Paper