Hi! My name is Tina. Currently, I'm a fourth-year PhD student in Computer Science at Stony Brook University, advised by Dr. Klaus Mueller . My research focuses on human-in-the-loop bias mitigation techniques and methods for auditing AI systems to ensure they do not cause unintended harm. I am a member of the BIAS-NRT group at Stony Brook, collaborating across disciplines to address bias and discrimination in both humans and AI. In addition to my PhD, I hold a graduate degree in Human-Centered Data Science and have taken advanced courses in Sociology and Psychology.

News

  • I will be joining Dr. Emily Ruth Diana 's lab at CMU for the summer of 2026.
  • I have been selected as a SPAR (Supervised Program for Alignment Research) research fellow for Fall 2025. I am working with Noah Y. Siegel on finding metrics for explanatory faithfulness.
  • I will be joining Dr. Ning Wang 's lab at the Institute for Creative Technologies at USC for the summer of 2024. We will be working on Explainable Self-Sware AI.

Publications

Do LLMs Ask the Right Questions? Evaluating GPT-Generated Surveys as Instruments for Measuring Social Attitudes
Tina Behzad, Wenbo Li, Reuben Kline, Klaus Mueller
LREC 2026 Workshop on Integrating NLP and Psychology to Study Social Interactions
An External Fairness Evaluation of LinkedIn Talent Search
Tina Behzad, Siddartha Devic, Vatsal Sharan, Aleksandra Korolova, David Kempe
AAAI 2026 (Oral, top ~8% in AI for Social Impacts track)
Beyond Predictions: A Study of AI Strength and Weakness Transparency Communication on Human–AI Collaboration
Tina Behzad, Nikolos Gurney, Ning Wang, David V Pynadath
HCI International 2025 – Late Breaking Papers, Lecture Notes in Computer Science, vol 16346.
FairPlay: A Collaborative Approach to Mitigate Bias in Datasets for Improved AI Fairness
Tina Behzad, Mithilesh Kumar Singh, Anthony J Ripa, Klaus Mueller
Proceedings of the ACM on Human-Computer Interaction (CSCW), 2025
Non-archival at Pluralistic Alignment Workshop, NeurIPS 2024
Reconciling Predictive Multiplicity in Practice
Tina Behzad, Sílvia Casacuberta, Emily Ruth Diana, Alexander Williams Tolbert
ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2025
Non-archival at Humans, Algorithmic Decision-Making and Society Workshop, ICML 2024
FRMDN: Flow-based Recurrent Mixture Density Network
Seyedeh Fatemeh Razavi, Reshad Hosseini, Tina Behzad
Expert Systems with Applications, 2024

Service

  • Reviewer IASEAI'26
  • Reviewer AIES 2026