Selected Works-In-Progress

• How Online Labor Matches Succeed or Fail: Evidence from Large-Scale Client–Freelancer Conversations
  with Wedad J. Elmaghraby, Ashish S. Kabra, and Kunpeng Zhang.
  • Supported by OpenAI Researcher Access Program (\$1,000), Smith Research Internal Grant (\$10,000)
  • Finalist, UMD Three-Minute Thesis (3MT) Competition 2025
• AI-Infused Nudges for Supply Chain Decision Making
  with Jane Yi Jiang and Wedad J. Elmaghraby.
  • Supported by Faculty–Student Research Award ($15,000) from the Graduate School

Working Papers

• Personalized Assortment Optimization for a Subscription Business Model of Experience Goods
  with Gah-Yi Ban, Wedad J. Elmaghraby, and L. Beril Toktay. Reject and Resubmit at Management Science – [SSRN]
  • Media Coverage: IB Knowledge
  • Presented at MSOM 2025, RMP 2025, Stitch Fix Algo Hours 2025, and Purdue Operations Conference 2023
• AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights
  with Gujie Li and Jane Yi Jiang. Under Review at Manufacturing & Service Operations Management – [SSRN]
  • Media Coverage: The New York Times, Business Insider, El Confidencial, The Register, Smith News, TRAILS News
  • Runner-up, Best Student Paper Award, Conference on Information Systems and Technology 2025
  • Finalist, Best Student Paper Presentation Award, AI in Business Conference at OSU 2025
  • Winner, INFORMS Minority Issues Forum Summer Webinar Competition 2025
  • Third Place, INFORMS K-12 Poster Competition 2025
  • Second Place, OR/MS Tomorrow Mini Poster Competition 2025
• Escaping the Nash Trap: Structural Estimation and Alignment of Strategic Reasoning in Large Language Models
  with Yongkang Duan, Jane Yi Jiang, and Jiding Zhang. – [SSRN]
  • Media Coverage: The New York Times
  • Accepted for presentation at the AI and Economics (AIE) Summer Conference

Computer Science Publications

Natural Language Processing Venues

• Escaping the Nash Trap: Structural Estimation and Alignment of Strategic Reasoning in Large Language Models
  Jiannan Xu $^{\dagger}$, Yongkang Duan $^{\dagger}$, Jane Yi Jiang, and Jiding Zhang. COLM 2026
  • Accepted to the Third Conference on Language Modeling
• Prompt Injection in Automated Résumé Screening with Large Language Models: Single and Multi-Injection Settings
  Preet Baxi, Jiannan Xu, Jane Yi Jiang, Stefanus Jasin. ACL 2026 Findings – [Paper] [Code]
  • In Findings of the Association for Computational Linguistics: ACL 2026
• Towards Conceptualization of “Fair Explanation”: Disparate Impacts of Anti-Asian Hate Speech Explanations on Content Moderators
  Tin Trung Nguyen $^{\dagger}$, Jiannan Xu $^{\dagger}$, Aayushi Roy, Hal Daumé III, and Marine Carpuat. EMNLP 2023 – [Paper] [Code]
  • In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

AI, Ethics, Society, and Law Venues

• Effort-Aware Fairness: Incorporating a Philosophy-Informed, Human-Centered Notion of Effort into Algorithmic Fairness Metrics
  Tin Trung Nguyen $^{\dagger}$, Jiannan Xu $^{\dagger}$, Zora Che, Phuong-Anh Nguyen-Le, Rushil Dandamudi, Donald Braman, Furong Huang, Hal Daumé III, and Zubin Jelveh. AAAI/ACM AIES 2025 – [Paper] [Poster] [Code]
  • In Proceedings of the 8th AAAI/ACM Conference on AI, Ethics, and Society
• Which Demographic Features Are Relevant for Individual Fairness Evaluation of U.S. Recidivism Risk Assessment Tools?
  Tin Trung Nguyen, Jiannan Xu, Phuong-Anh Nguyen-Le, Donald Braman, Jonathan Lazar, Hal Daumé III, and Zubin Jelveh. ICAIL 2025 – [Paper] [Code]
  • In Proceedings of the 20th International Conference on Artificial Intelligence and Law

$^{\dagger}$: Equal contribution