Huan Sun
Scholar

Huan Sun

Google Scholar ID: wIFkulcAAAAJ
Endowed CoE Innovation Scholar and Associate Professor, The Ohio State University
AgentsLarge Language ModelsNatural Language ProcessingAI
Citations & Impact
All-time
Citations
9,779
 
H-index
43
 
i10-index
89
 
Publications
20
 
Co-authors
9
list available
Resume (English only)
Academic Achievements
  • Paper publications: Best Paper Finalist at CVPR, Honorable Mention for Best Paper Awards at ACL (two papers), ACM SIGMOD Research Highlight Award, and the Best Paper Award from the IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Other awards: NSF CAREER Award, Google Research Scholar and Google Faculty Award, OSU Lumley Research Award, OSU President’s Research Excellence Award, and SIGKDD Ph.D. Dissertation Runner-Up Award, among others. Her team TacoBot won third place in the first Alexa Prize TaskBot challenge in 2022.
Research Experience
  • Led or co-led a series of foundational projects that helped shape the current landscape of AI agents, such as Mind2Web, SeeAct, and others. Committed to improving the safety of increasingly capable agents, exemplified by notable projects like AmpleGCG, EIA, and RedTeamCUA.
Education
  • Ph.D. in Computer Science from the University of California, Santa Barbara; B.S. in EEIS from the University of Science and Technology of China.
Background
  • Research interests: natural language processing and AI, with an emphasis on rigorously evaluating and advancing the capabilities and safety of autonomous agents powered by large language models (LLMs). Background: An endowed College of Engineering Innovation Scholar and associate professor with tenure in the CSE Department at The Ohio State University. She was a visiting scientist at the University of Washington.
Miscellany
  • Interested in finding multiple postdocs. Topics of interest include but are not limited to web and computer-use agents (both capability and safety), deep research systems, understanding transformers’ limitations in reasoning and generalization.