刘学军，教授，博士生导师。研究领域为人工智能及应用，在航空航天、流体力学、数值仿真等领域完成了20余项人工智能应用研究，积累了较为丰富的多学科交叉领域科研经验。合作主持“空气动力学与人工智能”跨学科国家级、省部级、企业合作项目二十余项，已发表学术论文60余篇。团队的学科交叉工作近两年做邀请报告三十余次，团队评校2019-2020年度“人工智能与空气动力学科交叉五好导学团队”，获第三届中央企业熠星创新创意大赛国家二等奖，2020年第五届江苏省科协青年会员创新创业大赛信息技术领域创新组唯一的一等奖，2022年度江苏省行业领域优秀科技进展（基础研究领域）。

 

 Welcome to join us. For more information, please refer to http://parnec.nuaa.edu.cn/liux. 

近年主要发表记录：

1.An Wei; Liu Jiawen; Lyu Hongqiang ; Liu Xuejun; Denoising graph neural network base on zero-shot learning for Gibbs phenomenon in high-order DG applications, Chinese Journal of Aeronautics, 2024, In publication.

2. Yu, Jian; Lyu, Hongqiang*; Xu, Ran; Ouyang, Wenxuan; Liu, Xuejun*; Flow2Mesh: A flow-guided data-driven mesh adaptation framework. Physics of Fluids, 2024, 36: 037124.

3. An W, Yu J, Lyu H, Liu X. An r-adaptive algorithm based on self-organizing maps for solving incompressible flows with high-order discontinuous Galerkin methods, Computers and Fluids, 2024, 270: 106160. 

4. 樊云翔; 艾化楠; 王明振; 曹楷; 刘学军; 吕宏强, 基于深度学习的水上飞机非定常水载荷重构, 航空学报, 2024, 45(20): 129882.

5. 林健; 吕宏强; 黄增辉; 刘子敬; 虞健; 刘学军.基于稀疏贝叶斯优化的翼型设计可解释性研究.空气动力学学报, 2024, In publication.

6. 刘嘉文;王明振;欧阳文轩;刘学军*;吕宏强*; 针对高阶间断伽辽金数值格式的Gibbs现象智能去噪方法;航空学报, 2024, 45(14): 129323.

7.  Yu, Jian; Wang, Mingzhen; Ouyang, Wenxuan; An, Wei; Liu, Xuejun*; Lyu Hongqiang*. Mesh Optimization Using an Improved Self-organizing Mechanism, Computers and Fluids, 2023, 266: 106062.

8.  Zhao S, Zhang L, Liu X. AE-TPGG: a novel autoencoder-based approach for single-cell RNA-seq data imputation and dimensionality reduction. Front Comput Sci. 2023;17(3):173902.

9.  Wang, Zhipeng; Liu, Xuejun; Yu, Jian; Wu, Haizhou; Lyu, Hongqiang, A general deep transfer learning framework for predicting the flow field of airfoils with small data, Computers and Fluids, 2022, 251: 105738. DOI: 10.1016/j.compfluid.2022.105738.

10.  Qu; Xiyao; Liu, Zijing; An, Wei; Liu, Xuejun; Lyu, Hongqiang; Dynamics-Disentangled Deep Learning Model for Long-Term Prediction of Unsteady Flow Field, Physics of Fluids, 2022, 34(9): 095128. DOI: 10.1063/5.0105887. 

11.  Liu, Zijing; Qu, Xiyao; Liu, Xuejun; Lyu, Hongqiang, Correlation-Concerned Bayesian Optimization for Multi-objective Airfoil Design, Aerospace Science and Technology. 2022, 129:107867. https://doi.org/10.1016/j.ast.2022.107867.

12.   Qu; Xiyao; Liu, Zijing; An, Wei; Liu, Xuejun; Lyu, Hongqiang; Predicting Pressure Coefficients of Wing Surface Based on the Transfer of Spatial Dependency, 2022, AIP Advances, 2022, 12(5): 055225. DOI: 10.1063/5.0093144.

13.  Qu; Xiyao; Liu, Zijing; An, Wei; Liu, Xuejun; Lyu, Hongqiang; Unsteady Flow Field Prediction: Understanding the Dynamics in an Intuitive Physics Way, The 26^th International Conference on Pattern Recognition (ICPR), August 21-25, 2022, Montréal Québec.

14.  Xuan, Yang; Lyu, Hongqiang; An, Wei; Liu, Jianhua; Liu, Xuejun*, A data-driven deep learning approach for predicting separation-induced transition of submarines, Physics of Fluids, 2022, 34(2). DOI: 10.1063/5.0079648. 

15. Shuchang Zhao, Li Zhang, Xuejun Liu. DAE-TPGM: A deep autoencoder network based on a two-part-gamma model for analyzing single-cell RNA-seq data[J]. Computers in Biology and Medicine, 2022, 146: 105578.

16.  Wu, Tingfan; Liu Xuejun; An, Wei; Huang Zenghui; Lyu, Hongqiang. A Mesh Optimization Method Using Machine Learning Technique and Variational Mesh Adaptation, Chinese Journal of Aeronautics, 2022, 35(3): 27-41. 

17.  H. Wu, X .Liu, W. An, H. Lyu. A generative deep learning framework for airfoil flow field prediction with sparse data, Chinese Journal of Aeronautics, 2022, 35(1): 470-484.https://doi.org/10.1016/j.cja.2021.02.012.

18.  Zijing Liu, Wei An, Xiyao Qu, Xuejun Liu, and Hongqiang Lyu, Portfolio-Based Bayesian Optimization for Airfoil Design, AIAA Journal, Vol. 59, No. 6 (2021), pp. 1975-1989 doi: doi/abs/10.2514/1.J059812.

19.  胡伟杰, 黄增辉, 刘学军,吕宏强, 基于自动核构造高斯过程的导弹气动性能评估, 航空学报, 2021, 42(4):524093.

20.  Li, J., Liu, X. and Zhang, D., Detecting differential transcript usage across multiple conditions for RNA-seq data based on the smoothed LDA model, Frontiers of Computer Science, 2021 15: 153319.

21.  Wu, H., Liu, X., An, W., Chen, S. and Lyu, H., A deep learning approach for efficiently and accurately evaluating the flow field of supercritical airfoils, Computers and Fluids, 2020 198: 104393.

22.  Yu, X. and Liu, X., Mapping RNA-seq reads to transcriptomes efficiently based on learning to hash method, Computers in Biology and Medicine, 2020 116: 103539.

23.  Sun, L, An, W., Liu, X. and Lyu, H., On developing data-driven turbulence model for DG solution of RANS, Chinese Journal of Aeronautics, 2019 32:1869-1884.

24. 石险峰, 刘学军, 张礼. PUseqClust: 一种RNA-seq数据聚类分析方法, 软件学报, 2019, 30: 2857-2868.

25.  Liu, Z., Liu, X. and Cai, X. A new hybrid aerodynamic optimization framework based on differential evolution and invasive weed optimization, Chinese Journal of Aeronautics, 2018 31:1437-1448.

2003.10 -- 2006.11
英国曼彻斯特大学       计算机科学       博士研究生毕业       哲学博士学位

1999.9 -- 2002.3
南京航空航天大学       计算机软件及理论       硕士研究生毕业       工学硕士学位

1995.9 -- 1999.6
南京航空航天大学       计算机及应用       大学本科毕业       工学学士学位

2007.5 -- 至今

南京航空航天大学计算机科学与技术学院