#  Lucy Lu Wang (University of Washington) 

 



####  calendar\_today Date and Time 

 **April 7, 2025** 

 11:30AM - 12:30PM EDT 

####  pin\_drop Location 

 **SEC 3.301/302/303**  



 

 [ Register Here arrow\_circle\_right ](https://tinyurl.com/CRCSSeminarLucyLuWang) 

 



 

   ![Lucy Lu Wang](/sites/g/files/omnuum6171/files/styles/hwp_1_1__360x360_scale/public/2025-03/profile12%20%281%29.jpg?itok=tgKDBVYZ) 

 

## Talk Title: Language Technologies to Improve Access to and Use of Medical Knowledge

 Rapid advancements in natural language processing (NLP) and LLMs have the potential to enhance accessibility and comprehension of medical knowledge. These technologies can adapt the language, format, tone, and interactivity of scientific and medical content, making it more understandable, engaging, and useful for different audiences like healthcare providers, researchers, and patients. In this talk, I examine how language models can bridge gaps in science communication by improving physical document accessibility, tailoring information to different levels of expertise and literacy, and supporting evidence synthesis. Additionally, I will discuss several ways we address the challenge of evaluating generated long-form text in high-expertise domains. Addressing these challenges can enhance the capabilities of these technologies in the context of medical information seeking and evidence-based decision-making.

## Speaker: Lucy Lu Wang

Lucy Lu Wang is an Assistant Professor at the University of Washington Information School, where she leads the Language Accessibility Research (LARCH) lab. She holds adjunct positions in the Paul G. Allen School of Computer Science & Engineering, Department of Biomedical Informatics & Medical Education, and Department of Human Centered Design & Engineering at the University of Washington, and is a Research Scientist at the Allen Institute for AI (Ai2). Her research investigates how to design and build language technologies to improve access to and understanding of information, especially in high-expertise domains like science and healthcare. Her work on supplement interaction detection, document accessibility, and academic publishing trends have been featured in Geekwire, Boing Boing, Axios, VentureBeat, and the New York Times. Prior to joining the UW, she was a Young Investigator at the Allen Institute for AI, and received her PhD in Biomedical Informatics and Medical Education from the University of Washington.



 

 



 

 

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