CV

Education

• B.S. in Shantou University, 2022

Internship experience

• Summer 2024: LLM assistant engineer
  • Puzhi Consulting Management (Shenzhen) Co., Ltd
  • Duties includes: Build a functional large language model (LLM) combining knowledge graph techniques for a consulting company from the ground up.
  • Supervisor: Xiaoqi Li

Publications

1. T. Lin#, S. Chen#, S. J. Harris, T. Zhao, Y. Liu, J. Wan, Investigating explainable transfer learning for battery lifetime prediction under state transitions. eScience, 2024, 100280.
2. N. Guo#, S. Chen#, J. Tao, Y. Liu, J. Wan, X. Li, Semi-supervised learning for explainable few-shot battery lifetime prediction. Joule, 2024.
3. S. Zhao, S. Chen, J. Zhou, C. Li, T. Tang, S. J. Harris, Li, X. Potential to transform words to watts with large language models in battery research. Cell Reports Physical Science, 2024, 5(3).
4. Y. Liu, S. Chen, P. Li, J. Wan, X. Li, Status, challenges, and promises of data‐driven battery lifetime prediction under cyber‐physical system context. IET Cyber‐Physical Systems: Theory & Applications, 2024
5. T. Lu, X. Zhai, S. Chen, Y. Liu, J. Wan, G. Liu, X. Li, Robust battery lifetime prediction with noisy measurements via totalleast-squares regression. Integration, 2024, 96, 102136.
6. X. Hu, D. Zuo, S. Cheng, S. Chen, Y. Liu, W. Bao, S. Deng, S.J. Harris, J. Wan, Ultrafast materials synthesis and manufacturing techniques for emerging energy and environmental applications. Chemical Society Reviews, 2023, 52(3):1103-1128.
7. Y. Wang, S. Chen, J. Xu, J. Wan, Y. Liu, X. Li; Casual Discovery for Rechargeable Battery Modeling Considering GroupLevel DAG Constraints, 50th Annual Conference of the IEEE Industrial Electronics Society (IECON), Chicago, USA, November 2024.