Fen Wang @ LAMDA, NJU-AI

Fen Wang
王芬
Fen Wang
Ph.D. Student, LAMDA Group
School of Artificial Intelligence
State Key Laboratory for Novel Software Technology
Nanjing University, Nanjing 210023, China
Supervisor: Prof. Kai Ming Ting

Biography

Currently I am a graduate student of School of Artificial Intelligence in Nanjing University and a member of LAMDA Group, led by professor Zhi-Hua Zhou. I received my B.Eng. degree from China University of Mining and Technology in June 2023, and my M.Sc. degree from Graduate School of China Electronics Technology Group Corporation in June 2026. In the same year, I was admitted to study for a Ph.D. degree in Nanjing University, under the supervision of Prof. Kai Ming Ting.

Research Interests

My research interests include Machine Learning and Data Mining.

Publications

[1] Fen Wang, Ming Ou, Bin Zhang, et al. Global hmF2 Parameter Prediction Modeling Based on COSMIC Satellite Data and SHAP Interpretable Method. Atmosphere, 2026, 17(4): 353.
[2] Fen Wang, Ming Ou, Qing-Lin Zhu, et al. Ionospheric foF2 Prediction Using an Interpretable XGBoost Model and COSMIC-1 and 2 Radio Occultation Data. Annals of Geophysics, 2026, 69(2): SA221-SA221.
[3] Ming Ou, Ya-Ping Guo, Fen Wang, et al. 基于深度学习的中国区域电离层 f0F2 短期预报方法. 空间科学学报, 2026, 46(3): 1-11.
[4] Fen Wang, Ming Ou, Long-Jiang Chen, et al. Global foF2 Prediction Modeling and Analysis Based on XGBoost Algorithm. In: Proceedings of the 2025 International Applied Computational Electromagnetics Society Symposium (ACES-China), IEEE, 2025: 1-3.
[5] Ming Ou, Fen Wang, Long Chen, et al. Data-Driven High-Frequency Ionospheric Ray-Tracing: A GNSS TEC-Assimilated NeQuick Model Approach. In: Proceedings of the 2025 International Applied Computational Electromagnetics Society Symposium (ACES-China), IEEE, 2025: 1-3.
[6] Fen Wang, Ming Ou, Ya-Ping Guo, et al. Validation of IRI and IRTAM Models Based on Global Ionosphere Radio Observatory Data. In: Proceedings of the 2024 14th International Symposium on Antennas, Propagation and EM Theory (ISAPE), IEEE, 2024: 1-4.
[7] Ming Ou, Fen Wang, Long Chen, et al. An Observational Data-Driven Analysis Model for Atmospheric Refraction Effects in Radar Systems. In: Proceedings of the 2024 14th International Symposium on Antennas, Propagation and EM Theory (ISAPE), IEEE, 2024: 1-3.

Contact

Email: wangf@lamda.nju.edu.cn

Office: C203, School of Artificial Intelligence Building, Nanjing University Xianlin Campus

Address: State Key Laboratory for Novel Software Technology, Nanjing University, Xianlin Campus Mailbox 603, 163 Xianlin Avenue, Qixia District, Nanjing 210023, China