Hi! I am a Ph.D. candidate in the School of Computing at UConn, advised by Dr. Dongjin Song.
My research focuses on developing generalizable and interpretable AI for time series analysis, spanning multi-modal data, general-purpose models, and real-world learning constraints. I work closely with leading research institutions and industry partners, including NEC Labs America, Morgan Stanley, and Mayo Clinic.
I am currently on the job market, actively seeking faculty and research positions. If you are interested in my research or would like to discuss potential opportunities, please feel free to reach out :)
Recent News
06/2026: One paper is accepted (Oral) to AIDataSci @ KDD 2026.
TacitFlow: Learning Workflow Representations for Tacit-Knowledge-Grounded MLE Agents
06/2026: One paper is accepted to Forecast @ ICML 2026.
TimeRouter: Efficient and Adaptive Routing of Time Series Foundation Models
05/2026: I started my summer research internship at GE Aerospace Research - Knowledge Discovery & High Assurance Systems.Â
05/2026: I received Taylor L. Booth Graduate Fellowship, the highest honor awarded by the School of Computing.
09/2025: Two papers are accepted to NeurIPS 2025.
TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop