Yushan Jiang
Yushan Jiang
Ph.D. Candidate in Computer Science, School of Computing, University of Connecticut
Ph.D. Candidate in Computer Science, School of Computing, University of Connecticut
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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 deep learning methods 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.
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.
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
06/2025: I started my summer research internship at Mayo Clinic - AI & I Department.
05/2025: One paper is accepted to KDD 2025.
Multi-modal Time Series Analysis: A Tutorial and Survey
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