2012.09 - 2018.06，中国地质大学（武汉），地球探测与信息技术专业，博士（硕博连读）

2016.09 - 2017.09，加拿大不列颠哥伦比亚大学（UBC），电气工程与计算机科学专业，联合培养（国家留学基金委资助）

2008.09 - 2012.06，中国地质大学（武汉），测控技术与仪器专业，学士

2018.07 - 至今，中国地质大学（武汉），自动化学院，特任副教授 2016.09 - 2017.09，加拿大不列颠哥伦比亚大学（UBC），电气工程与计算机科学系，ISDPRL实验室，研究助理

主持国家重点研发计划项目子课题1项（60万）、国家自然科学基金青年科学基金1项（23万）、陆军研究院XXX国防重点实验室基金1项（20万）、中央高校杰出人才培育基金1项（20万）、中国地质科学院地球物理地球化学勘查研究所专项资金项目1项（15万）；以骨干成员参与国家自然科学基金面上项目、国家重大科学仪器设备开发专项、总装备预先研究项目、武汉市科技计划项目、NRC加拿大国家研究委员会专项资金项目、NASA美国国家航空航天局开放课题等项目1. 国家自然科学基金青年科学基金：融合多源场信息的磁温漂抑制及磁误差校正方法研究，2020.01-2022.12，主持

2. 陆军研究院XXX国防重点实验室基金：基于地磁多参量融合的XXX方法研究，2019.01-2020.12，主持

3. 中央高校杰出人才培育基金：多源磁测数据融合机理研究，2018.07-2021.07，主持

4. 中国地质科学院地球物理地球化学勘查研究所专项资金项目：页岩气开采水力压裂电位监测仪研究，2013.01-2014.12 ，主持

5. 国家重点研发计划 “高精度地球物理场观测设备研制” 课题2：“自动化地磁绝对观测系统和高精度磁力仪研制” 子课题，2018.12-2021.12 ，主持

6. 武汉市科技计划项目：多传感器自适应融合的智能磁力仪研究，2019.07-2021.12 ，技术骨干（第三）

7. 国家自然科学基金面上项目：基于优化动态核极化的新型Overhauser磁力仪研究，2015.01-2018.12，技术骨干

8. 国家重大科学仪器设备开发专项：海洋地磁场矢量测量仪开发与应用，2015.01-2018.12，技术骨干

9. 解放军总装备部装备预先研究项目：动态激发质子磁法XXX技术研究，2012.01-2013.12，技术骨干

10. NRC加拿大国家研究委员会研究项目：地下输油管道无损探伤技术研究，2016.01-2017.12，技术骨干


11. NASA美国国家航空航天局开放课题：复合材料损伤程度智能预测研究，2016.01-2017.12，技术骨干

发表SCI/EI论文30余篇[1] Huan Liu, Wang Luo, Haobin Dong, et al. Design and implementation of a tuning-matching framework for a high-sensitivity broad band proton precession magnetometer sensing coil, IEEE Sensors Journal, 2019.

[2] Huan Liu, Haobin Dong, Jian Ge, et al. High-precision sensor tuning of proton precession magnetometer by combining principal component analysis and singular value decomposition, IEEE Sensors Journal, 19(21): 9688-9696, 2019.

[3] Huan Liu, Junchi Bin, Haobin Dong, et al. Adaptive pre-whiten filtering for the free induction decay transversal signal in weak magnetic detection, Review of Scientific Instruments, 90(10): 104502, 2019.

[4] Huan Liu, Haobin Dong, Jian Ge, et al. Efficient performance optimization for the magnetic data readout from a proton precession magnetometer with low rank constraint, IEEE Transactions on Magnetics, 55(8): 9300104, 2019.

[5] Huan Liu, Zheng Liu, Shuo Liu, et al. A nonlinear regression application via machine learning techniques for geomagnetic data reconstruction processing, IEEE Transactions on Geoscience and Remote Sensing, 57(1): 128-140, 2019.

[6] Huan Liu, Zheng Liu, Haobin Dong, et al. Recurrent neural network-based approach for sparse geomagnetic data interpolation and reconstruction, IEEE Access, 7(1): 33173-33179, 2019.

[7] Huan Liu, Haobin Dong, Jian Ge, et al. A fusion of principal component analysis and singular value decomposition based multivariate denoising algorithm for free induction decay transversal data, Review of Scientific Instruments, 90(3): 035116, 2019.

[8] Huan Liu, Zheng Liu, Brandon Taylor, et al. Matching pipeline In-line inspection data for corrosion characterization, NDT & E International, 101: 44-52, 2019.

[9] Huan Liu, Haobin Dong, Jian Ge, et al. Apparatus and method for efficient sampling of critical parameters demonstrated by monitoring an Overhauser geomagnetic sensor, Review of Scientific Instruments, 89(12): 125109, 2018.

[10] Huan Liu, Haobin Dong, Zheng Liu, et al. A comprehensive study on the weak magnetic sensor character of different geometries for proton precession magnetometer, Journal of Instrumentation, 13(9): T09003, 2018.

[11] Huan Liu, Haobin Dong, Zheng Liu, et al. Application of Hilbert-Huang decomposition to reduce noise and characterize for NMR FID signal of proton precession magnetometer, Instruments and Experimental Techniques, 61(1): 55-64, 2018.

[12] Huan Liu, Haobin Dong, Zheng Liu, et al. Noise characterization for the FID signal from proton precession magnetometer, Journal of Instrumentation, 12(7): P07019, 2017.


[13] Huan Liu, Haobin Dong, Zheng Liu, et al. Construction of an Overhauser magnetic gradiometer and the applications in geomagnetic observation and ferromagnetic target localization, Journal of Instrumentation. 12(10): T10008, 2017.

[14] Huan Liu, Haobin Dong, Jian Ge, et al. An improved tuning control algorithm based on SVD for FID signal, Journal of Advanced Computational Intelligence and Intelligent Informatics, 21(1): 133-138, 2017.

[15] Huan Liu, Haobin Dong, Jian Ge, et al. Research on a secondary tuning algorithm based on SVD & STFT for FID signal, Measurement Science and Technology, 27(10): 105006, 2016.

[16] 刘欢, 董浩斌, 葛健, 等. Overhauser磁力仪探头激发频率测试仪研制, 电子学报, 45(2): 1272-1280, 2017.

[17] 刘欢, 董浩斌, 葛健, 等. 基于Overhauser效应的磁场梯度探测器, 仪器仪表学报, 36(3): 592-600, 2015.

[18] Haobin Dong, Huan Liu (共同第一作者，通讯作者), Jian Ge, et al. A high-precision frequency measurement algorithm for FID signal of proton magnetometer, IEEE Transactions on Instrumentation and Measurement, 65(4): 898-904, 2016.

[19] Yuefei Huang, Jian Ge, Haobin Dong and Huan Liu (通讯作者). An automatic wide-band 90 phase shifter for optically pumped cesium magnetometers, IEEE Sensors Journal, 17(23): 7928-7934, 2017.

[20] Cheng Zhang, Haobin Dong, Jiahao Wang, Jian Ge, Huan Liu (通讯作者), et al. A low error rate BCH-based encoder-decoder approach for electromagnetic measurement while drilling system, IEEE Access, 7(1): 34599-34608, 2019.

会议论文
[1] Huan Liu, Haobin Dong, Jian Ge, et al. A new F-PCASVD based multivariate denoising algorithm for FID transversal data, IEEE International Conference on Instrumentation and Measurement Technology (I2MTC), 1-6, 2019.

[2] Huan Liu, Yihao Liu, Shuo Liu, et al. What can machine learning do for geomagnetic data processing? A reconstruction application, IEEE International Conference on Instrumentation and Measurement Technology (I2MTC), 1-6, 2018.

[3] Huan Liu, Shuo Liu, Zheng Liu, et al. Prognostics of damage growth in composite materials using machine learning techniques, IEEE International Conference on Industrial Technology (ICIT), 1042-1047, 2017.

[4] Huan Liu, Haobin Dong, Jian Ge, et al. A high-precision proton magnetometer based on a multi-channel frequency measurement, IEEE International Conference on Instrumentation and Measurement Technology (I2MTC), 1-6, 2016.

[5] Huan Liu, Haobin Dong. Research and developed of magnetic field gradient detector based on the nuclear Overhauser effect, IEEE International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC), 330-333, 2015.

学术报告


2019 IEEE I2MTC，作分会场报告，奥克兰，新西兰

• A new F-PCASVD based multivariate denoising algorithm for FID transversal data

2018 IEEE I2MTC，张贴海报，休斯顿，美国

• What can machine learning do for geomagnetic data processing? A reconstruction application

• A resonant cavity based on birdcage coil for Overhauser geomagnetic sensor

2017 IEEE ICIT，作分会场报告，多伦多，加拿大


• Prognostics of damage growth in composite materials using machine learning techniques

• Experimenting capacitive sensing techniques for structural integrity assessment

2016 ITCA，作分会场报告，东京，日本

• An improved tuning control algorithm based on SVD for FID signal

2016 IEEE I2MTC，张贴海报，台北，中国台湾

• A high precision proton magnetometer based on a multi-channel frequency measurement

2015 IEEE IMCCC，张贴海报，秦皇岛，中国

• Research and developed of magnetic field gradient detector based on the nuclear Overhauser ef

1] 提高质子旋进类传感器调谐精度和信噪比的系统及方法, 申请号：201910578198.4

[2] 提高质子磁旋进信号信噪比的系统及方法, 申请号：201910580050.4

[3] 一种适用于质子磁旋进信号的噪声抑制系统及方法, 申请号：201910809909.4

[4] 基于MEMS弱磁传感器阵列的低功耗安检探测系统及方法, 申请号：201910810531.X

[5] 一种基于量化时延法提高FID信号测频精度的方法及电路, 申请号：201710002829.9

软件著作权

[1] 基于MEMS磁传感器的金属安检门系统数据采集软件V1.0, 登记号：2019SR1001751

[2] 基于主成分分析和奇异值的拉莫尔旋进信号噪声抑制软件V1.0, 登记号：2019SR0989846

[3] 质子磁旋进信号噪声抑制软件V1.0, 登记号：2019SR0756583


[4] 磁异常探测系统数据采集软件V1.0, 登记号：2019SR0757495