• 2014 ~ 2018，索邦大学（法国） 博士

• 2010 ~ 2013，中国核动力研究设计院 硕士

• 2006 ~ 2010，清华大学 学士

• 2022 ~ 至今，上海交通大学巴黎卓越工程师学院 工程科学计算与数字孪生、AI for Science

• 2021 ~ 2022，中国核动力研究设计院 核反应堆系统数字孪生、数据挖掘研究

• 2018 ~ 2020，中国核动力研究设计院 数字反应堆研究、核能系统数据挖掘研究

• 2013 ~ 2014，中国核动力研究设计院 核反应堆在线监测系统研究

1、《C程序与算法分析》 本科生，48学时，3学分（合上）
2、《数理基础综合实践》，本科，16学时，2学分（合上）
3、《最优化与数值分析》硕士生，48学时，2学分
4、《信息通信前沿项目2》 硕士生，64学时，4学分（合上）
5、《重大工程管理与工业软件》 硕士生，32学时，2学分（合上）

• 人工智能：AI for Science、机器学习替代模型、图像超分 工程科学计算：反问题、数据同化、模型降阶、模型校正 数字孪生：模型研究、软件研发、复杂工业系统设施在线监测、健康管理及预测性维护 核工程：数字化反应堆、中子噪声分析、反应堆物理

• 中核集团领创科研项目“xx数据同化和不确定性分析技术” , 科研项目 , 省部级 , 课题主持

• 国防科技工业核动力技术创新中心项目“基于节块法的堆芯中子噪声建模关键技术研究” , 科研项目 , 国家级 , 课题主持

• 上海市自然科学基金面上项目“基于实时数字孪生的核反应堆堆芯在线监测技术研究” , 科研项目 , 省部级 , 课题主持

• 中国核动力研究设计院“任意时刻开展通量图试验软件开发” , 科研项目 , 省部级 , 课题主持

• 中国原子能科学研究院“XX模型开发及UI设计” , 科研项目 , 省部级 , 课题主持

• 国家自然科学基金面上项目“多尺度反应堆物理动态行为预测关键技术研究” , 科研项目 , 国家级 , 参与

• XX核电1、2号机组，XX核电5、6号机组反应性辅助决策系统研发 , 科研项目 , 省部级 , 负责人

• 核反应堆系统设计技术国防科技重点实验室稳定支持项目“基于卷积神经网络的长寿命小型堆芯物理关键参数快速评价模型研究” , 科研项目 , 国家级 , 课题主持

• 科工局核能开发项目 , 科研项目 , 国家级 , 负责人

• 国家自然科学基金青年科学基金项目“基于模型降阶和数据同化的反应堆在线监测系统探测机理研究” , 科研项目 , 国家级 , 课题主持

• 国防科技工业核动力技术创新中心项目“基于动态数据驱动的在线监测系统研究” , 科研项目 , 国家级 , 课题主持

• 中国核动力研究设计院产业开发项目“xxx运行数据管理系统研发” , 科研项目 , 省部级 , 负责人

• ZF数字堆项目“基于数据驱动的堆芯物理计算程序研究” , 科研项目 , 国家级 , 课题主持

• 龚禾林;刘威震;吴屈;李庆;李天涯;廖鸿宽;钟旻霄;王江宇;赵文博;张世全;陈长. 核反应堆物理计算数据同化研究进展[J].火箭军工程大学学报,2024,38(02):57-71.

• 龚禾林;洪历展;赵文博;王江宇;廖鸿宽;李天涯;钟旻霄;李庆;陈长.基于“全局-局部”搜索的核反应堆运行孪生反问题求解[J].原子能科学技术,2024,58(07):1424-1431.

• Yang, Q. H., Yang, Y., Deng, Y. T., He, Q. L., Gong, H. L., & Zhang, S. Q. (2023). Physics-constrained neural network for solving discontinuous interface K-eigenvalue problem with application to reactor physics. Nuclear Science and Techniques, 34(10), 161.

• Gong Helin, Zhang Shiquan, Yvon Maday. THE OPTIMUM OF EIM MAGIC POINTS AND THE LEAST-SQUARES FORM[J]. Journal on Numerica Methods and Computer Applications, 2023, 44(1): 25-36.

• Yang, Y.; Gong, H.*; He, Q.*; Yang, Q.; Deng, Y.; Zhang, S. On the uncertainty analysis of the data-enabled physics-informed neural network for solving neutron diffusion eigenvalue problem. Nuclear Science and Engineering. 2023. DOI: 10.1080/00295639.2023.2236840.[SCI]

• Gong, H.; Zhu, T.*; Chen, Z.; Wan, Y. and Li, Q*. Parameter identification and state estimation for nuclear reactor operation digital twin. Annals of Nuclear Energy,180(2023):109497.[SCI]

• Yang, Y.; Gong, H.*; Zhang, S.*; Yang, Q.; Chen, Z.; He, Q. and Li, Q. A data-enabled physics-informed neural network with comprehensive numerical study on solving neutron diffusion eigenvalue problems. Annals of Nuclear Energy, 2023, 183, 109656.[SCI]

• Li,W.; Gong, H.; Zang, C*. Solution of Neutron Diffusion Problems by Discontinuous Galerkin Finite Element Method With Consideration of Discontinuity Factors. Journal of Nuclear Engineering and Radiation Science, 2023, 9(3), 031503. [SCI]

• Gong, H.; Cheng, S.; Chen, Z.; Li, Q.*; Quilodrán-Casas, C.; Xiao, D. and Arcucci, R. An efficient digital twin based on machine learning SVD autoencoder and generalised latent assimilation for nuclear reactor physics. Annals of Nuclear Energy. 179(2022):109431.[SCI]

• Gong, H.; Chen, Z. and Li, Q*. Generalized Empirical Interpolation Method with H1 Regularization: Application to Nuclear Reactor Physics. Frontiers in Energy Research. 2022, 9:804018. [SCI]

• Gong, H.; Cheng, S.; Chen, Z. and Li, Q*. Data-Enabled Physics-Informed Machine Learning for Reduced-Order Modeling Digital Twin: Application to Nuclear Reactor Physics. Nuclear Science and Engineering, Taylor & Francis, 2022, 196, 668-693.[SCI]

• Gong, H.*; Chen, Z.; Maday, Y. and Li, Q. Optimal and fast field reconstruction with reduced basis and limited observations: application to reactor core online monitoring. Nuclear Engineering and Design, 2021,377:111113. [SCI]

• Chen, W.; Di, Y.; Zang, J.; Zhang, C.*; Gong, H.; Xia, B.; Quan, Y.; Wang, L. Study of non-intrusive model order reduction of neutron transport problems. Annals of Nuclear Energy. 2021, 162: 108495. [SCI]

• Gong, H.*; Chen,Z; Wu,W; Peng, X; Li,Q*. Neutron noise calculation: A comparative study between SP3 theory and diffusion theory. Annals of Nuclear Energy, 2021,156:108184. [SCI]

• Gong, H.*; Chen,W; Zhang,C.Y*; Chen,G. Fast solution of neutron diffusion problem with movement of control rods. Annals of Nuclear Energy, 2020, 149:107814. [SCI]

• Gong, H.*; Yu,Y; Li,Q*. Reactor power distribution detection and estimation via a stabilized gappy proper orthogonal decomposition method. Nuclear Engineering and Design, 2020, 370: 110833. [SCI]

• Gong, H.; Yu,Y; Li,Q*; Quan, C.Y*. An inverse-distance-based fitting term for 3D-Var data assimilation in nuclear core simulation. Annals of Nuclear Energy, 2020, 141: 107346.[SCI]

• Argaud, J.P; Bouriquet, B; Gong, H.*; Maday,Y; Mula,O. Sensor placement in nuclear reactors based on the Generalized Empirical Interpolation Method. Journal of Computational Physics, 2018, 363: 354-370. [SCI]

• Peng,X*; Li,Q; Zhao,W; Gong, H.; Wang,K. Robust filtering for dynamic compensation of self-powered neutron detectors. Nuclear Engineering and Design,2014, 280: 122-129. [SCI]

• Gong, H.; Maday,Y; Mula,O; Taddei,T. PBDW method for state estimation: error analysis for noisy data and nonlinear formulation. arXiv e-prints, p. arXiv:1906. 00810, Jun 2019.[EI]

• H. Gong; Q. Li, Q. Liu, X. Li, Z. Lu, J. Wang, Y. Xie, Z. Chen, Y. Yu, X. Peng, K. Liu, R. Guo, B. Zhang and X. Wang. 2D1D Coupled Power Reconstruction Method for On-line Monitoring of PWRs. Atomic Energy Science and Technology, 2021,55(02): 272-278. [EI]

• H. Gong, Z. Chen, W. Zhao, X. Peng, Q. Li and Y. Yu. Development of a neutron noise simulator with SP3 approximation. Nuclear Science and Engineering. 2021, 41(03)491-499.

• H. Gong, Z. Chen, Q. Li, S. Cheng. Study on a Data-Enabled Physics-Informed Reactor Physics Operational Digital Twin. Nuclear Power Engineering, 2021, 42(S2):48-53. [EI]

• Z. Zhang, H. Liao, Q. Li, H. Gong, Z. Chen, X. Li, Q. Liu. Error Analysis of LPD On-line Monitoring System in HPR 1000. Nuclear Power Engineering, 2020,41(2): 11-15. [EI]

• H. Gong, Q. Li, Y. Yu, J.P. Argaud, B. Bouriquet, Y. Maday and O. Mula. A new data-driven approach for reconstruction with noisy data and physical constraints: application to nuclear reactor physics. In Proceedings of ICAPP 2019.

• H. Gong, Q. Li, Y. Yu, and Y. Maday. “EIM in the frame of least-squares optimal interpolation method.” Annual meeting of Science and Technology on Reactor System Design Technology Laboratory. Chengdu, China, November 6, 2018.

• H. Gong, J.P. Argaud, B. Bouriquet, Y. Maday and O. Mula. Monitoring flux and power in nuclear reactors with data assimilation and reduced models. In Proceedings of M&C 2017.

• J.P. Argaud, B. Bouriquet, H. Gong, Y. Maday and O. Mula. Stabilization of (G)EIM in Presence of Measurement Noise: Application to Nuclear Reactor Physics. In Marco L. Bittencourt, Ney A. Dumont, and Jan S. Hesthaven, editors, Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2016, pages 133-145, Cham, 2017. Springer International Publishing.

• H. Gong, J. P. Argaud, B. Bouriquet, and Y. Maday. The Empirical Interpolation Method applied to the neutron diffusion equations with parameter dependence. In Proceedings of PHYSOR 2016.

• P. Zhang, H. Gong and K. Wang. Preliminary Study on Neutronics Characteristics of Thorium-based Supercritical Water-cooled Fast Reactor. The 5th Int. Sym. SCWR (ISSCWR-5). Vancouver, British Columbia, Canada, March 13-16, 2011.

• Li, H., Lu, J., Ji, H., Hong, L., & Gong, H. (2023). A noise and vibration tolerant resnet for field reconstruction with sparse sensor. Communications in Computational Physics.

• Shi, B., Qiu, Q., Gong, H., Li, Q., & Luo, Y. (2023, August). Noninvasive Data-Driven Prediction of Reactor Power Field: An MLP-Based Approach. In 2023 IEEE Smart World Congress (SWC) (pp. 1-6). IEEE.

• Zeng, J. Q., Zhang, H. X., Gong, H. L., & Luo, Y. T. (2023). Ensemble Bayesian method for parameter distribution inference: application to reactor physics. Nuclear Science and Techniques, 34(12), 199.

• Liu, J., Gong, H., Wang, Z., & Li, Q. (2023). Uncertainty analysis of dynamic mode decomposition for xenon dynamic forecasting. Annals of Nuclear Energy, 194, 110106.

• Gong, H. L., Li, H., Xiao, D., & Cheng, S. (2024). Reactor field reconstruction from sparse and movable sensors using Voronoi tessellation-assisted convolutional neural networks. Nuclear Science and Techniques, 35(5), 43.

• Yang, Y., Gong, H., He, Q., Yang, Q., Deng, Y., & Zhang, S. (2024). On the uncertainty analysis of the data-enabled physics-informed neural network for solving neutron diffusion eigenvalue problem. Nuclear Science and Engineering, 198(5), 1075-1096.

• GONG, H., HONG, L., ZHAO, W., WANG, J., LIAO, H., LI, T., ... & CHEN, Z. (2024). Global-local Search Based Inverse Problem Solver for Reactor Operation Digital Twin. Atomic Energy Science and Technology, 58(7), 1424-1431.

• Hong, L. Z., Gong, H. L., Ji, H. J., Lu, J. L., Li, H., & Li, Q. (2024). Optimizing near-carbon-free nuclear energy systems: advances in reactor operation digital twin through hybrid machine learning algorithms for parameter identification and state estimation. Nuclear Science and Techniques, 35(8), 135.

• Liu, X., Wang, Z., Ji, H., & Gong, H. (2024). Application and comparison of several adaptive sampling algorithms in reduced order modeling. Heliyon, 10(15).

• Xu, B., Li, H., Zhang, L., & Gong, H. (2024). A Comprehensive Deep Learning–Based Approach to Field Reconstruction in Reactor Cores. Nuclear Science and Engineering, 1-15.

• Jianpeng Liu, Zhiyong Wang, Qing Li. & Helin Gong.A Hybrid Data Assimilation and Dynamic Mode Decomposition Approach for Xenon Dynamic Prediction of Nuclear Reactor Cores.Nuclear Science and Engineering, Taylor & Francis, 2024, 0, 1-19.

• 余书沛;吕皓琛;龚禾林;张世全;贺巧琳;杨宇;杨其洪;曾未.求解中子扩散方程特征值问题的深度神经网络方法和软件[J/OL].计算物理,1-14[2024-11-20].

• 张音音;于婷;张睿志;金文蕾;罗应婷;朱升峰;何辉;叶国安;龚禾林.基于机器学习的30%TBP/煤油-硝酸体系中主要组分的分配比预测研究[J/OL].原子能科学技术,1-10[2024-11-20]

• 基于卡尔曼滤波的 铑自给能探测器信号延迟消除方法，2014-06-08，CN103871524B[P]，龚禾林,李庆,刘启伟,陈长,李向阳,卢宗健,王金雨,宫兆虎

• 基于卡尔曼滤波的 铑自给能探测器信号延迟消除方法.，2014-06-18，CN 103871525B[P]，龚禾林,李庆,刘启伟,陈长,李向阳,卢宗健,王金雨,宫兆虎

• 基于 IIR 滤波的铑 自给能探测器信号延迟消除方法，2015-09-02，CN104882182B[P]，龚禾林,陈长,彭星杰,赵文博,刘启伟,李向阳,李庆,于颖锐

• 基于局 部非线性修正的堆芯功率分布在线重构方法及系统，2021-09-12，CN113421669B[P]，龚禾林,李庆,于颖锐,陈长,赵文博,彭星杰,刘同先,娄磊,巨海涛,吉文浩

• 一种基于 SP3 方程的反应堆中子噪声分析方法，2021-08-27，CN113312791B[P]，龚禾林,周冰燕,李庆,于颖锐,彭星杰,陈长,赵文博,赵晨,娄磊,刘琨,巨海涛

• 一种用于反应的 LPD 和 DNBR 在线保护和监测的实现方法，2020-11-24，CN110322976B[P]，杨戴博,陈乐,李文平,黄有俊,龚禾林,刘启伟,王金雨,谢运利,李向阳,刘余,田宇

• 用于反应堆运行参数优化的数据同化方法、系统及终端，2023-11-10，CN115408861 B，龚禾林,李庆,陈长,钟旻霄

• 基于模型降阶和数据同化的堆芯功率分布在线监测方法及系统，2021-09-17，CN113409975B[P]，李庆,龚禾林,陈长,赵文博,于颖锐,彭星杰,宫兆虎,刘琨,周冰燕,刘佳艺,张斌,王冬勇

• 一种反应堆堆芯核设计系统及应用，2022-06-17，CN112668165B[P]，钟旻霄,李天涯,李庆,于颖锐,龚禾林,宫兆虎,黄世恩,廖鸿宽,陈飞飞,卢迪

• 四川省侨联特评专家委，委员，2021-01至今

• 国防科技工业核动力技术创新中心基础理论部，学术秘书，2019-01~2022-01

• 华龙一号堆芯在线监测关键技术研发四川省科学技术进步二等奖

• 中国核能行业协会科学 技术二等奖,第九完成人

• 中国专利优秀奖, 第五完成人

• 中核集团优秀国防科技报告