Part of the TPC Seminar Series
Speaker: Xuan Wang, Assistant professor in the department of computer science at Virginia Tech
Date: Wednesday, August 12, 2026
Time: 1:00 p.m. (CT)
Location: Virtual (https://argonne.zoomgov.com/j/1608919794?pwd=tONTcW6sOu6Z9iMxahSWAtfty7CaTK.1)
Abstract:
Recent advances in large language models have shown impressive capabilities across scientific domains and societal applications, but their size and proprietary nature often limit accessibility and reproducibility. In this talk, I will present our work on developing small, open-source, multi-modal language model agents that can reason, plan, and act in diverse scientific and societal contexts. I will discuss methods for designing small but highly effective language models, integrating multi-modal inputs, and coordinating multi-agent interactions to achieve complex tasks. I will also highlight real-world applications in science and society, emphasizing transparency, reproducibility, and accessibility.
Biography:
Dr. Xuan Wang is an assistant professor in the department of computer science at Virginia Tech, and a faculty member of the Sanghani Center for Artificial Intelligence and Data Analytics. She develops scalable and reliable multi-agent foundation model systems for decision-making in complex multimodal real-world environments. Her work is motivated by high-stakes domains such as science and healthcare. Her work has been recognized by the NSF CAREER Award (2025), NVIDIA Academic Grant (2025), Cisco Research Award (2025-2026), and the NAACL Best Demo Paper Award (2021). She received her Ph.D. in Computer Science, M.S. in Statistics, and M.S. in Biochemistry from the University of Illinois at Urbana-Champaign, and her B.S. in Biological Science from Tsinghua University, China.