Yue Guo
 
 614 E. Daniel Street
Room 4131
Champaign, IL 61820
Assistant Professor @ UIUC. Previously: UW/AI2/Google/MSR/JHU.
Assistant Professor, School of Information Sciences 
 Affiliate, Siebel School of Computing and Data Science 
 Affiliate, Health Care Engineering Systems Center
Hello! I am specializing in Health Informatics and Natural Language Processing (NLP). My research focuses on leveraging AI/NLP to enhance the accessibility and personalization of health information, bridging the gap between complex medical knowledge and diverse healthcare consumers, clinicians, and researchers. Trained as a physician and epidemiologist before transitioning to health informatics, I bring a multidisciplinary perspective to AI-driven solutions in medicine.
Ongoing projects:
- š„ Health Information Accessibility & Personalization
- 𩺠LLM Reasoning
- š¤ Trustworthy AI for Medical Applications
I will be recruiting multiple PhD and master students from the iSchool (primarily) and CS programs starting in Fall 2026. If youāre interested in working with me, please read through mentorship section carefully and complete the Google form. Please note that I will not be responding to emails regarding applications. Iām always excited to hear from motivated students! šāØ
news
| Oct 7, 2025 | Iāll be at AMIA in Atlanta, November 15ā18āļøš! If youāre curious about my work, thinking about future research opportunities, or just want to chat about ideas, Iād love to meet up. Drop me an email and letās connect! | 
|---|---|
| Sep 20, 2024 | Excited to share that our paper for plain language summarization evaluation has been accepted to #EMNLP2024! š Iāll be in Miami for the conferenceāfeel free to reach out if youād like to chat! š© | 
| Jan 15, 2024 |  Check out my new publication: Retrieval Augmentation of Large Language Models for Lay Language Generation | 
selected publications
-   Are LLM-generated plain language summaries truly understandable? A large-scale crowdsourced evaluationarXiv preprint arXiv:2505.10409, 2025 Are LLM-generated plain language summaries truly understandable? A large-scale crowdsourced evaluationarXiv preprint arXiv:2505.10409, 2025
 
  
  
 