About Me

I am a PhD Candidate in the Department of Information Systems and Cyber Security at the University of Texas at San Antonio (UTSA), advised by Dr. Anthony Rios. I received my M.S. in Applied Mathematics and Statistics from the University of Colorado Denver and B.S. in Statistics from Minzu University of China. I have broad multidisciplinary research interests that bring together Natural Language Processing (NLP), Large Language Models (LLMs), and Human-Computer Interaction (HCI) to address real-world challenges in healthcare and society. My work focuses on fairness, bias detection, and promoting equity in AI for healthcare. I have published in prestigious venues across NLP, biomedical informatics, and computational social science, including NAACL, COLING, ICWSM, BioNLP, Clinical NLP, and JAMIA. I was awarded the Future Research Leaders in Artificial Intelligence (30 national) by the University of Michigan.

🔍 Research Overview

My research focuses on Natural Language Processing (NLP), Large Language Models (LLMs), and Human-Computer Interaction (HCI) to advance Responsible AI for healthcare decision‑making and community well‑being. My main contribution is developing a comprehensive framework to identify, measure, and mitigate bias in biomedical and social applications.

What is Responsible AI for Healthcare: Responsible AI ensures that algorithms operate fairly and transparently across all stages, from data collection to model inference to deployment, by actively detecting and reducing ethical harms such as bias, privacy issues, and unintended consequences.

Why Responsible AI Matters: In healthcare, even minor biases can lead to misdiagnoses, unequal treatment recommendations, and exacerbated health disparities. By rigorously measuring bias in data and models, and speculating about future bias and its consequences, we can reduce risks before deployment by examining how AI performs across different patient contexts, especially edge cases where misalignment with users’ needs can lead to unintended harm.

How to Develop Responsible AI: I focus on three main areas:

1. Clinical Informatics: We develop methods to extract Social Determinants of Health (SDoH), such as income, housing, and employment, from unstructured EHR notes and turn them into structured data, like tables or graphs. Real-world bias goes beyond race, age, and gender, and capturing these social factors helps us better understand long-term impacts and improve clinical decisions.

2. Public Health Informatics: We develop novel prompting strategy to understand how the public perceives news headlines and how hidden bias in content such as implicit framing or unbalanced reporting, can shape public opinion and diverge from real-world data. We also develop benchmarks to evaluate when, how, and why biomedical AI systems fail, especially across different identities like race or gender?

3. Human-Centered Design: Inspired by ``Black Mirror’’, we develop a multi-agent system that uses LLMs to simulate virtual environments and character interactions. It generates user stories that reflect potential harms and benefits, helping people speculate about future bias and its consequences before AI models are developed and deployed.

📚 Publications

• Bike Frames: Understanding the Implicit Portrayal of Cyclists in the News
  Xingmeng Zhao, Xavier Walton, Suhana Shrestha, Anthony Rios
  In: Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2025

• Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations
  James Ford, Xingmeng Zhao, Dan Schumacher, Anthony Rios
  In: Proceedings of the 31st International Conference on Computational Linguistics (COLING 2025)

• A Comprehensive Study of Gender Bias in Chemical Named Entity Recognition Models
  Xingmeng Zhao, Ali Niazi, Anthony Rios
  In: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024)

• Translating Natural Language Specifications into Access Control Policies by Leveraging Large Language Models
  Sherifdeen Lawal, Xingmeng Zhao, Anthony Rios, Ram Krishnan, David Ferraiolo
  Forthcoming in: IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications

• UTSA-NLP at ChemoTimelines 2024: Evaluating Instruction-Tuned Language Models for Temporal Relation Extraction
  Xingmeng Zhao, Anthony Rios
  In: Proceedings of ClinicalNLP Workshop at NAACL 2024

• Improving Expert Radiology Report Summarization by Prompting Large Language Models with a Layperson Summary
  Xingmeng Zhao, Tongnian Wang, Anthony Rios
  arXiv preprint arXiv:2406.14500, June 2024

• A Marker‑based Neural Network System for Extracting Social Determinants of Health
  Xingmeng Zhao, Anthony Rios
  Journal of the American Medical Informatics Association (JAMIA), 2023

• UTSA-NLP at RadSum23: Multi-modal Retrieval-Based Chest X-Ray Report Summarization
  Tongnian Wang, Xingmeng Zhao, Anthony Rios
  In: Proceedings of BioNLP Workshop at ACL 2023
  *These authors contributed equally to the paper.

• BabyStories: Can Reinforcement Learning Teach Baby Language Models to Write Better Stories?
  Xingmeng Zhao, Tongnian Wang, Sheri Osborn, Anthony Rios
  In: Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning (CoNLL) at EMNLP 2023

• Turning Stocks into Memes: A Dataset for Understanding How Social Communities Can Drive Wall Street
  Richard Alvarez, Paras Bhatt, Xingmeng Zhao, Anthony Rios
  In: Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2022

• UTSA-NLP at SemEval-2022 Task 4: An Exploration of Simple Ensembles of Transformers, Convolutional, and Recurrent Neural Networks
  Xingmeng Zhao, Anthony Rios
  In: Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)

👨‍🏫 Teaching Experience

• Instructor, IS 1413 Excel for Business Information Systems, Spring 2023
• Instructor, IS 2053 Programming Languages I with Scripting, Spring 2024
• Instructor, IS 1403 Business Info Systems Fluency, Fall 2024

📄 CV

Download my CV.

For the most up-to-date list of my publications, please visit my Google Scholar Profile.