I am currently a PhD student at the University of Georgia (UGA) under the supervision of Dr. Fei Dou. My research interests include deep learning applications in time series, signal processing, and biomedical applications. I am particularly interested in applications related to everyday life, such as computer vision and reinforcement learning.

Education

• B.S. in Computer Science and Engineering, University of Liverpool, 2021
• M.S. in Scientific and Data-intensive Computing, University College London, 2022
• Ph.D. in progress, University of Georgia, 2024–present (supervisor: Dr. Fei Dou)

Work experience

• 2024–present: PhD Student
  • University of Georgia
  • Supervisor: Dr. Fei Dou
• 2023-2024: Research Assistant
  • Hong Kong University of Science and Technology
  • Duties included: Research
  • Supervisor: Professor Dit-Yan

Papers

• Peak-R1: Instruction-Tuned Large Language Models for Robust J-Peak Detection in Cardiomechanical Signals (J Li, Y Zhang, Z Zeng, J Chen, X Zhang, J Lu, WZ Song, F Dou). NeurIPS 2025 Workshop on Learning from Time Series for Health. [link]

• Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges (H Lu, L Fang, R Zhang, et al.). arXiv preprint arXiv:2507.19672, 2025. [pdf]

• Genbench: A Benchmarking Suite for Systematic Evaluation of Genomic Foundation Models (Z Liu, J Li, S Li, Z Zang, C Tan, Y Huang, Y Bai, SZ Li). arXiv preprint arXiv:2406.01627, 2024. [pdf]

• MGTST: Multi-scale and Cross-channel Gated Transformer for Multivariate Long-term Time-series Forecasting (J Li, Z Zhou, DY Yeung). 2024. [link]

• Principal component analysis machine learning to determine membership of globular cluster M56, Master thesis, University College London, 2022. [pdf]

• A teaching app to demonstrate Hebb’s learning rule, Bachelor thesis, University of Liverpool, 2021. [pdf]

See Publications for the full list.