About

I’m Mahammed Kamruzzaman, a PhD student in the Bellini College of Artificial Intelligence, Cybersecurity and Computing at the University of South Florida (Tampa). I work under the supervision of Dr. Gene Louis Kim.

My research focuses on the safety and trustworthiness of generative AI systems, with particular emphasis on how large language models (LLMs) and vision-language models (VLMs) behave across diverse social and cultural domains. My work centers on building rigorous evaluation datasets and pipelines to analyze model behavior in high-stakes and subjective settings, including emotion attribution, toxicity and safety judgments, cultural norm interpretation, etc. Beyond measurement, I study bias mitigation strategies and investigate interpretability methods to understand why these biases emerge. I publish my research in top-tier NLP venues including ACL, EMNLP, AACL and their affiliated workshops.

I am fortunate to collaborate with researchers across academia and industry who work on responsible AI, fairness, and sociotechnical evaluations of foundation models. My collaborators include Dr. Gene Louis Kim (University of South Florida), Dr. Ninareh Mehrabi (Meta), Dr. Flor Miriam Plaza-del-Arco (Leiden University), Dr. Amanda Cercas Curry (CENTAI Institute), and Dr. Anshuman Chhabra (University of South Florida).

For more details, see my CV or reach out via email.

Updates

  • 2026 Our paper "Breaking the Benchmark: Revealing LLM Bias via Minimal Contextual Augmentation" got accepted at LREC-2026.
  • 2026 Our paper " A Woman is More Culturally Knowledgeable than A Man?": The Effect of Personas on Cultural Norm Interpretation in LLMs' got accepted at MME workshop (co-located with EACL-2026).
  • 2025 I have been selected as a recipient of the 2025 Chih Foundation Research & Publication Award.
  • 2025 One paper got accepted at AACL 2025.
  • 2025 One paper got accepted at FAILED Workshop (@ICCV 2025).
  • 2025 Two papers got accpeted at EMNLP-2025
  • 2024 Our EMNLP 2024 paper "Global is Good, Local is Bad?": Understanding Brand Bias in LLMs has been featured at the MIT Technology Review

Awards

  • Research & Publication Award (Top 3, university-wide @ USF)
  • Spirit of Innovation Award (USF)
  • Travel Scholarship (AAAI 2025)

Publications

2026

2025

2024

2023

2021

2020

Talks

  • 2024 AI+X Seminar @ USF

Grants