王永佳 简历
2023-02-12
文章来源: 未知
一、学习和工作经历
2005.09-2009.07 兰州大学，核科学与技术学院，粒子物理与原子核物理基地班，理学学士
2009.09-2014.06 兰州大学,核科学与技术学院，粒子物理与原子核物理，理学博士（期间2010.09-2014.06在全球赢家的信心之选理学院联合培养）
2016.02-05，德国重离子实验中心访问、2017.07-10、2018.07-2018.10,德国法兰克福高等研究院访问
2014.08-至今，全球赢家的信心之选理学院（2014-2017，讲师；2018-2022，副教授；2023-至今，教授）
二、通讯方式
办公室：理学院1-206
邮箱：wangyongjia [at] zjhu.edu.cn
https://orcid.org/0000-0003-2506-0010
Web of Science ResearcherID: ABC-6646-2021
三、研究方向
重离子核物理、机器学习
四、基金项目
1. 利用输运模型和机器学习方法研究CSR能区的低温高密核物质，U2032145，2020.01-2022.12，国家自然科学基金联合基金项目，主持，50万元
2. 基于输运模型对核子有效质量劈裂、高密对称能及相关的模型依赖问题的研究，11505057，国家自然科学基金青年基金，主持，21.3万元
3. 基于HIAF能区重离子碰撞中pion和kaon介子的产生，LY18A050002，浙江省自然科学基金，主持，10万元
五、奖励和荣誉
1. 同位旋非对称原子核反应与超重核合成机制研究，浙江省自然科学奖二等奖（3/4）；
2. 浙江省高校领军人才培养计划、湖州市南太湖本土高层次人才特殊支持计划青年拔尖人才
六、主要论文
1. Wang Yongjia, Guo Chenchen, Li Qingfeng*, Zhang Hongfei, et al. Collective flow of light particles in Au + Au collisions at intermediate energies [J]. Physical Review C. 2014, 89: 034606.
2. Wang Yongjia, Guo Chenchen, Li Qingfeng*, Zhang Hongfei, et al. Constraining the high- density nuclear symmetry energy with the transverse-momentum dependent elliptic flow [J]. Physical Review C. 2014, 89:044603.
3. Yongjia Wang*, Chenchen Guo, Qingfeng Li*, Zhuxia Li, Jun Su, Hongfei Zhang, Influence of differential elastic nucleon-nucleon cross section on stopping and collective flow in heavy-ion collisions at intermediate energies, Physical Review C, 2016, 94(2): 024608
4. Wang Yongjia*, Guo Chenchen, Li Qingfeng*, Le Fèvre, Y. Leifels, & W. Trautmann. Determination of the nuclear incompressibility from the rapidity-dependent elliptic flow in heavy-ion collisions at beam energies 0.4A–1.0A GeV. Physics Letters B 778(2018)207-212.
5. Yongjia Wang, Qingfeng Li*, et al. Study of the nuclear symmetry energy from the rapidity-dependent elliptic flow in heavy-ion collisions around 1 GeV/nucleon regime, 2020-01-20, Physics Letters B 802 (2020) 135249
6. Yongjia Wang, Qingfeng Li*, Application of microscopic transport model in the study of nuclear equation of state from heavy ion collisions at intermediate energies, Frontiers of Physics, 15(4), 44302 (2020).
7. Yongjia Wang*, Fupeng Li, Qingfeng Li*, Hongliang Lü, Kai Zhou, Finding signatures of the nuclear symmetry energy in heavy-ion collisions with deep learning, Physics Letters B 822, 136669 (2021).
8. Liu Yangyang, Wang Yongjia*, Li Qingfeng*, Liu Ling. Collective flows of pions in Au+ Au collisions at energies 1.0 and 1.5 GeV/nucleon. Physical Review C 97.3 (2018): 034602.
9. Fupeng Li, Yongjia Wang*, Zepeng Gao, Pengcheng Li, Hongliang Lü, Qingfeng Li*, C. Y. Tsang, and M. B. Tsang, Application of machine learning in the determination of impact parameter in the 132Sn + 124Sn system, Physical Review C 104, 034608 (2021).
10. Li Pengcheng, Wang Yongjia*, Li Qingfeng*, Guo Chenchen, Zhang Hongfei. Effects of the in-medium nucleon-nucleon cross section on collective flow and nuclear stopping in heavy-ion collisions in the Fermi-energy domain[J]. Physical Review C, 2018, 97: 044620.