TLDR: Dr. Xuan Wang, an Assistant Professor at Virginia Tech, has been awarded the prestigious NSF CAREER Award in July 2025 for her pioneering work in using AI for scientific information extraction from vast text datasets. Her research also significantly contributes to building trustworthy AI in healthcare, demonstrated by a study where her team’s large language models outperformed trained nurses in emergency room patient triage.
Virginia Tech’s Department of Computer Science is celebrating a significant achievement as Assistant Professor Dr. Xuan Wang was recently honored with the National Science Foundation (NSF) CAREER Award in July 2025. This esteemed award will bolster her research focused on leveraging artificial intelligence to extract scientific information from massive text data, a critical step towards accelerating scientific discovery.
Dr. Wang, who is also a core faculty member of the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, specializes in Natural Language Processing, Data Mining, AI for Sciences, and AI for Healthcare. Her work aims to develop principled data-driven approaches that require minimal human effort for effective and scalable model learning.
One of her notable contributions lies in ‘Building trust in AI-powered healthcare.’ In a collaborative study with Children’s National Hospital in Washington, D.C., Dr. Wang’s team explored the application of large language models (LLMs) for triaging emergency room patients. The results were compelling, with the AI models demonstrating a 10 percent higher accuracy rate than a trained nurse in assessing the urgency of a doctor’s intervention .
Addressing the crucial aspect of adoption in clinical settings, Dr. Wang emphasized the importance of ‘trustworthy AI.’ She stated, ‘A very big research direction is trustworthy AI.’ To foster this trust, AI systems must provide transparent explanations for their decisions, such as citing lab results or medical guidelines. Furthermore, her research explores the use of multiple LLMs, known as multi-agent models, for collaborative decision-making. ‘Each model can be dedicated to a certain small task, and in this multi-agent framework, they can talk to each other to further confirm, as a team, that they are not doing anything incorrectly,’ Wang explained . This collaborative approach enhances accuracy and builds confidence in AI’s recommendations.
Beyond the CAREER Award, Dr. Wang’s recent accolades in 2025 include an Nvidia Academic Grant and a Cisco Research Award. Her lab has also seen four papers accepted by EMNLP’25, focusing on LLM agents, multi-modal learning, and trustworthy LLMs. Additionally, her team received an awardable designation from the DARPA ERIS Marketplace for their pitch video on ‘Towards Intelligent and Resilient U.S. Pharmaceutical Supply Chains via Multi-Agent AI,’ and Google Cloud Research Credits to support multi-agent language model systems .
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Dr. Wang’s academic background includes a Ph.D. in Computer Science, and two Master’s degrees in Statistics and Biochemistry, all from the University of Illinois at Urbana-Champaign. She earned her Bachelor’s degree in Biological Science from Tsinghua University, China, laying a strong interdisciplinary foundation for her innovative work in AI.
