Zelin He

Zelin He

AS Intern @Amazon & AWS AI | PhD Candidate & Fellow @PSU

I am a Ph.D. Candidate at Penn State. I am closely working with Amazon DST & AWS AI, focusing on large language and vision-language models for time-series reasoning, working with Boran Han and Matthew Reimherr. I am advised by Dr. Runze Li and in collaboration with Dr. Ying Sun from the EECS department, where we develop transfer-learning and meta-learning methods for modeling large-scale, crowd-sourced datasets.

Signals & Time Series Understanding and Reasoning
Signals & Time Series Understanding and Reasoning.

Publications and Preprints

  • Harnessing Vision-Language Models for Time Series Anomaly Detection (2025+) [Paper]
    • Zelin He, Sarah Alnegheimish, Matthew Reimherr
    • Proceedings of the Fortieth AAAI Conference on Artificial Intelligence (AAAI) (Oral)
  • Understanding the Accuracy-Communication Trade-off in Personalized Federated Learning (2025) [Paper] [Code]
    • Xin Yu*, Zelin He*, Ying Sun, Lingzhou Xue, Runze Li
    • Proceedings of The 42nd International Conference on Machine Learning (ICML)
  • M2AD: Detecting Anomalies in Heterogeneous Multivariate Time Series from Multiple Systems (2025)
    • Sarah Alnegheimish, Zelin He, Matthew Reimherr, Akash Chandrayan, Abhinav Pradhan, Luca D’Angelo
    • Proceedings of The 28th International Conference on Artificial Intelligence and Statistics (AISTATS)
  • TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression (2024) [Paper] [Code]
    • Zelin He, Ying Sun, Jingyuan Liu, Runze Li
    • Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS)
  • Weakly-supervised Multi-sensor Anomaly Detection with Time-series Foundation Models (2024)
    • Zelin He, Matthew Reimherr, Sarah Alnegheimish, Akash Chandrayan
    • NeurIPS 2024 TSALM Workshop
  • AdaTrans: Feature-wise and Sample-wise Adaptive Transfer Learning for High-dimensional Regression (2024+) [Paper] [Slides] [Poster] [Talk (in Chinese)]
    • Zelin He, Ying Sun, Jingyuan Liu, Runze Li

📧 If you’re interested in my research, don’t hesitate to send me an email!! Let’s chat more about it.

Reviewer Experience

  • ICML 2024
  • ICLR 2025
  • NeurIPS 2025
  • JASA
  • TNNLS
  • JCGS

Education

  • Ph.D. in Statistics, Pennsylvania State University, 2022 - Present.
  • B.S. in Statistics, Beijing Normal University, 2018 - 2022.

Awards

  • University Graduate Fellowship, 2023
  • Early Pass of the Doctoral Theory Qualifying Exam, 2022
  • Paul M. Doty Distinguished Graduate Fellowship, 2022
  • Verne M. Willaman Distinguished Graduate Fellowships in Science, 2022
  • National Scholarship, 2021