About me

I am a second-year Computer Science PhD student at the University of Maryland, College Park (UMD), fortunately advised by Prof. Hal Daumé III and Prof. Zubin Jelveh, who care and foster conceptual creativity. My research interests include AI fairness, trustworthiness, natural language processing (NLP), machine learning (ML), and law. My currently most focused research direction is law-informed fairness, including but not limited to two broad questions:

  1. How to identify the current stances and knowledge gaps of heterogeneous legal sources that regulate a. AI in general, and b. the fairness of AI-involved decision-making processes in particular?
  2. How to design new concepts, technical experiments, and/or human studies to address those law-informed AI fairness knowledge gaps while minimizing disruptiveness to existing legal principles?

Funding and Awards

  1. DOJ/NIJ Graduate Research Fellowship 2023 ($166,500 over 3 years; topic: Operationalizing the Individual versus Group Fairness Dichotomy for Recidivism Risk Assessment: US Legal Challenges and Technical Proposals)
  2. Funded Proposal: Effort-aware Fairness (approx. $98,500 for one year; project conceptualized and proposal drafted by me, then refined and submitted with Donald Braman, Furong Huang and my PhD Advisors to NIST-NSF TRAILS)
  3. Dean’s Fellowship ($5000 over 2 years)

Publications

  1. Tin Nguyen, Jiannan Xu, Aayushi Roy, Hal Daumé III and Marine Carpuat. Towards Conceptualization of “Fair Explanation”: Disparate Impacts of anti-Asian Hate Speech Explanations on Content Moderators. EMNLP 2023. 6-minute, pre-recorded presentation and poster.
  2. Navita Goyal, Connor Baumler, Tin Nguyen and Hal Daumé III. The Impact of Explanations on Fairness in Human-AI Decision Making: Protected vs Proxy Features. Accepted at IUI 2024.