PhD Student · University of Georgia

I study deep learning for time series, signal processing, and biomedical applications, with a particular interest in systems that connect machine learning research to everyday life.

Focus Deep learning for time series

Modeling sequential, cardiomechanical, biomedical, and signal-rich data.

Current Role PhD student at UGA

Advised by Dr. Fei Dou and working across AI, health, and data science.

Research Style Applied, careful, human-centered

Building models and benchmarks that make complex data more useful.

Research Interests

My research interests include deep learning applications in time series, signal processing, and biomedical applications. I am especially drawn to practical AI problems involving computer vision, reinforcement learning, health data, and scientific discovery.

Education

2024-present
Ph.D. in progress

University of Georgia · Supervisor: Dr. Fei Dou

2022
M.S. in Scientific and Data-intensive Computing

University College London

2021
B.S. in Computer Science and Engineering

University of Liverpool

Experience

2024-present
PhD Student

University of Georgia · Supervisor: Dr. Fei Dou

2023-2024
Research Assistant

Hong Kong University of Science and Technology · Supervisor: Professor Dit-Yan Yeung

Selected Papers

ADLGen: Synthesizing Symbolic, Event-Triggered Sensor Sequences for Smart-Home Human Activity Modeling

W You, H Jiang, J Li, Z Liu, T Liu, J Lu, F Dou. Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems.

Read the paper

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.

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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.

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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.

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MGTST: Multi-scale and Cross-channel Gated Transformer for Multivariate Long-term Time-series Forecasting

J Li, Z Zhou, DY Yeung. 2024.

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See Publications for the full list.