Postdoctoral researcher at IROM Department, McCombs School of Business, The University of Texas at Austin, 2024-
Research analyst, Boston Medical Center, Boston, MA, 2017-2018
Ph.D. in Economics, University of Washington, 2018-2024
Visiting student at IROM Department, McCombs School of Business, The University of Texas at Austin, 2023-2024
M.A in Economics, Boston University, 2016-2017
B.S in Mathematical Economics, Shanghai University of Finance and Economics, 2012-2016
Causal inference, Machine learning/AI, Applied econometrics, Non-parametric estimation, Optimal transport theory.
Yifan Yu, Wendao Xue, Lin Jia, and Yong Tan, "When Emotion AI Meets Strategic Users," Accepted at Management Science.
Amresh D. Hanchate, K. Sophia Dyer, Michael K. Paasche-Orlow, Souvik Banerjee, William E. Baker, Mengyun Lin, Wendao Xue, James Feldman, “Disparities in Emergency Department Visits Among Collocated Racial/Ethnic Medicare Enrollees,” Annals of Emergency Medicine, 2019.
Wendao Xue, Huidi Ma, Yifan Yu, and Ashish Agarwal, "GenAI-Enabled Causal Study of Unstructured Data: Application in LLMs and Emotion Analysis," 2024 ISS Cluster Best Paper Award Runners-up; INFORMS Workshop on Data Science Best Student Paper Nomination.
Jingwen Zhang, Wendao Xue, Yifan Yu, and Yong Tan, “Debiasing Machine-Learning- or AI-Generated Regressors in Partial Linear Models,” California Econometrics Conference 2023 Popular Vote Poster Award, Major revision at Infromation System Research.
Wendao Xue, Juan Wang, Yifan Yu, and Yong Tan, “Understanding the Dynamics between Urban Transportation Modes and Air Pollutants: Evidence from China’s COVID-19 Shock,” R&R at Production and Operations Management.
Wendao Xue, “Correcting Strategic Misreporting Behavior On Outcomes in Estimating Treatment Effect.”
Xiaohong Chen, Yanqin Fan, and Wendao Xue (eq. contributed), “Identification and Estimation of Treatment Effects in the Non-overlap Region.”
"Navigating Knowledge Tasks with AI: Evidence from a Field Experiment at KPMG" with Wen Wen, Ashish Agarwal, and Anitesh Barua.
"The Spread of the Video DeepFakes on Social Media," with Vasundhara Sharma, Ashish Agarwal, and Anitesh Barua.
"GenAI-Enabled Causal Study of Unstructured Data: Application in LLMs and Emotion Analysis," with Huidi Ma, Yifan Yu, and Ashish Agarwal, the EEO Workshop at Harvard Business School 2025, Conference on Information Systems and Technology (CIST) 2025, Big 2025 XII+MIS Research Symposium; CRL@NeurIPS 2024 workshop; SFLLM@NeurIPS 2024 workshop; Business and Gen AI Conference 2024.
"The Spread of the Video DeepFakes on Social Media," with Vasundhara Sharma, Ashish Agarwal, and Anitesh Barua, Biz AI Conference 2025.
“Correcting Machine Learning Generated Variable Bias in Regression Models,” with Jingwen Zhang, Yifan Yu, and Yong Tan, the EEO Workshop at Harvard Business School 2025, American Causal Inference Conference (ACIC) 2024; Biz AI Conference (BizAi-Conf) 2024; California Econometrics Conference 2023, MIT Conference on Digital Experimentation (CODE@MIT) 2023, Conference on Artificial Intelligence, Machine Learning, and Business Analytics (AIMLBA) 2023, Conference on Information Systems and Technology (CIST) 2023, INFORMS Workshop on Data Science (WDS) 2023, China Marketing International Conference (CMIC) 2023.
“Correcting Strategic Misreporting Behavior On Outcomes in Estimating Treatment Effect,” BIRS OT and DRO Workshop 2024, MIT Conference on Digital Experimentation (CODE@MIT) 2023, California Econometrics Conference 2023, 2023 INFORMS Workshop on Data Science, 2023 INFORMS DMDA Workshop.
"COVID-19, Urban Transportation, and Air Pollution," with Juan Wang, Yifan Yu, and Yong Tan, International Conference on Information Systems (ICIS) 2021, Manufacturing & Service Operations Management (MSOM) Conference 2021.
"Domestic Outbreak of COVID-19 Pandemic Heard Disproportionate Female Voices in News," with Juan Wang, Yifan Yu, Yong Tan, and Zhihan Li, Conference on Information Systems and Technology (CIST) 2022.
“Identification and Estimation of Treatment Effects in the Limited Overlap Region,” with Xiaohong Chen and Yanqin Fan, Econometrics and Optimal Transport Workshop 2023, INFORMS 2021.
"GenAI-Enabled Causal Study of Unstructured Data: Application in LLMs and Emotion Analysis," INFORMS Annual Meeting (INFORMS) 2024 (scheduled)
"GenAI-Enabled Causal Study of Unstructured Data: Application in LLMs and Emotion Analysis," Tongji Univerity, 2024
"GenAI-Enabled Causal Study of Unstructured Data: Application in LLMs and Emotion Analysis," Fudan Univerity, 2024
“Correcting Strategic Misreporting Behavior On Outcomes in Estimating Treatment Effect,” BIRS OT and DRO Workshop 2024
Journal Reviewer for Journal of Econometrics
PC member for INFORMS Workshop on Data Science
Conference Reviewer for ICIS, CIST
PhD Student Mentor: Department of Economics, School of Art and Science, University of Washington.
Richard B. Wesley Endowed Graduate Fellowship, 2023.
Henry T. Buechel Memorial Scholarship, 2022.