CV

Education

• B.S. in HuZhou, HuZhou University, 2014-2018
• M.S. in HangZhou, Zhejiang University of Technology, 2018-2021
• Ph.D in WuHan, Central China Normal University, 2021-present

Main Research Interests

• Machine Learning; Theory in nuclear physics; Heavy-ion Collisions

Skills

• Fortran
• Python(Pytorch, Keras and tensorflow)
  • Machine learning
  • Automatic differentiation program
• C++&Mathematical&Matlab

Publications

Application of artificial intelligence in the determination of impact parameter in heavy-ion collisions at intermediate energies

Fu-Pung Li, Yongjia Wang, Hongliang Lü et al. "Application of artificial intelligence in the determination of impact parameter in heavy-ion collisions at intermediate energies." J. Phys. G: Nucl. Part. Phys. 47, 115104 (2020).

Application of machine learning in the determination of impact parameter in the $^{132}Sn$ + $^{124}Sn$ system

Fu-Pung Li, Yongjia Wang, Zepeng Gao et al. "Application of machine learning in the determination of impact parameter in the $^{132}Sn$ + $^{124}Sn$ system." Physical Review C. 104. 034608 (2021).

Finding signatures of the nuclear symmetry energy in heavy-ion collisions with deep learning

Yongjia Wang, Fu-Peng Li, Qingfeng Li, Hong-Liang Lü, Kai Zhou. "Finding signatures of the nuclear symmetry energy in heavy-ion collisions with deep learning." Phys. Lett. B. 822,136669 (2021).

Deep-learning quasi-particle masses from QCD equation of state

Fu-Peng Li, Hong-Liang Lü, Long-Gang Pang, Guang-You Qin. "Deep-learning quasi-particle masses from QCD equation of state." Phys. Lett. B. 844,138088 (2023).