Qr code
中文
Liu Huan

Associate professor
Master Tutor


Honors and Titles : 荣获2018年度中国地质大学(武汉)“优秀博士毕业生”;荣获2016年度博士研究生“国家奖学金”;荣获2010年度本科生“国家奖学金”
Gender : Male
Date of Birth : 1989-02-20
Alma Mater : China University of Geosciences (Wuhan)
Education Level : Faculty of Higher Institutions
Degree : Doctoral Degree in Engineering
Status : Employed
School/Department : School of Automation
Date of Employment : 2018-07-01
Discipline : Measurement and control technology and instrument automation
Business Address : Room 103, Institute of Geophysics & Geomatics
Room 809, School of Automation

Contact Information : 027-67883097
Email :
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Personal Profile


About Me


Hello, my name is Huan Liu, you can call me "Sky" which seems like not a traditional English name. I am currently an Associate Professor at the School of Automation, China University of Geosciences, Wuhan, China. I was supported from the China Scholarship Council, Ministry of Education, China, studying at Electrical Engineering and Computer Science, School of Engineering, University of British Columbia, Kelowna, Canada, as a Joint Training Ph.D. student, from 2016 to 2017. I received my Ph.D. degree with Geodetection and Information Technology, Institute of Geophysics & Geomatics, China University of Geosciences, Wuhan, China, in 2018.  

I have been involved in developing intelligent geophysical instruments, especially, the proton magnetometer and the Overhauser magnetometer. My research interest lies in intelligent geophysical instrumentation, weak signal processing, data mining and machine learning applications with the focuses on weak magnetic detection and nondestructive testing. 


Educational Background


2012.09 - 2018.06  Doctor of Philosophy,  China University of Geosciences, Wuhan, China

2016.09 - 2017.09  Visiting Scholar,  University of British Columbia, Kelowna, BC, Canada

2008.09 - 2012.06  Bachelor of Engineering,  China University of Geosciences, Wuhan, China


Research Experience


2018.07 - Present   Associate Professor School of Automation, China University of Geosciences, Wuhan, China

                       • Multivariate noise reduction algorithm for FID signal based on the fusion of PCA and SVD

                       • Intelligent adaptive noise suppression in Larmor precession signal using deep convolutional neural networks

                       • Recurrent neural network-based approach for geomagnetic data interpolation with missing traces


2016.09 - 2017.09  Research Assistant,  Intelligent Sensing, Diagnostic and Prognostic Research Laboratory, Kelowna, BC, Canada

                       • Machine learning based approaches for damage growth prediction in composite materials

                       • Matching pipeline anomaly features via machine learning techniques from ILI data

                       • Geomagnetic data reconstruction via machine learning techniques

                       • Quantification of capacitive sensing imaging for pipe pitting corrosion measurement


2014.09 - 2018.06  Research Assistant,  Advanced Intelligent Geophysical Instrumentation Research Laboratory, Wuhan, China

                       • New-generation Overhauser magnetometer based on optimization of dynamic nuclear polarization

                       • Hydraulic fracturing potential monitoring system for shale gas exploitation

                       • Improved signal processing algorithms for an Overhauser magnetometer

                       • High resolution temperature measurement technique


2012.09 - 2014.08  Research Assistant, Science and Technology on Near-Surface Detection Laboratory, Wuxi, China

                       • Detection technology of near-surface unexploded ordnance

                       • Magnetic field gradient detector based on nuclear Overhauser effect


Publications


Journal


[1]   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, 2019. 

[2]   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. 

[3]   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.

[4]   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. 

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

[6]   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. 

[7]   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. 

[8]   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 magnetometerInstruments and Experimental Techniques, 61(1):55-64, 2018. 

[9]   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. 

[10]  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. 

[11]  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. 

[12]  Huan Liu, Haobin Dong, Jian Ge, et al. Research and develop of the test apparatus for measuring the excitation frequency of Overhauser magnetometer probe, Acta Electronica Sinica , 45(2): 1272-1280, 2017. 

[13]  Haobin Dong, Huan Liu (Co-first author,Corresponding author), 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. 

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

[15]  Huan Liu, Haobin Dong, Jian Ge, et al. Magnetic field gradient detector based on the nuclear Overhauser effect, Chinese Journal of Scientific Instrument, 36(3): 592-600, 2015. 

[16]  Bingjie Bai, Huan Liu, Jian Ge, et al. Research on an improved resonant cavity for Overhauser geomagnetic sensor, IEEE Sensors Journal, 18(7): 2713-2721, 2018. 

[17]  Jian Ge, Haobin Dong, Huan Liuet al. Overhauser geomagnetic sensor based on the dynamic nuclear polarization effect for magnetic prospecting, Sensors, 16(6): 806-822, 2016. 

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

[19]  Haobin Dong, Shuting Hu, Jian Ge, Huan Liuet al. A high-precision and fast-sampling frequency measurement method based on FPGA carry chain for airborne optically pumped cesium magnetometer, Review of Scientific Instruments, 89(7): 075001, 2018. 

[20]  Jian Ge, Chengda Lu, Haobin Dong, Huan Liuet al. The detection technology of near-surface UXO based on magnetic gradient method and Overhauser sensor, Chinese Journal of Scientific Instrument, 36(5): 38-50, 2015. 

[21]  Jian Ge, Xiangyu Qiu, Haobin Dong, Wang Luo, Huan Liuet al. Short-time and high-precision measurement method for Larmor frequency of marine Overhauser sensor, IEEE Sensors Journal, 18(4): 1442-1448, 2018. 


Conference


[1]  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.

[2]  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.

[3]  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.

[4]  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.

[5]  Zheng Liu, Huan Liu. Experimenting capacitive sensing techniques for structural integrity assessment, IEEE International Conference on Industrial Technology (ICIT), 922-927, 2017.

[6]  Fang Shi, Xiang Peng, Huan Liuet al. Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods, Smart Structures and NDE for Industry 4.0, 1060207, 2018. 

[7]  Bingjie Bai, Haobin Dong, Jian Ge, Huan Liuet al. A resonant cavity based on birdcage coil for Overhauser geomagnetic sensor, IEEE International Conference on Instrumentation and Measurement Technology (I2MTC), 1-6, 2018.


Professional Activities


Presentations


ICIT-2017 

TitlePrognostics of Damage Growth in Composite Materials Using Machine Learning Techniques

VenueHilton Toronto, 145 Richmond Street West, Toronto, Ontario, M5H 2L2, Canada

Time9:00 AM - 9:30 AM


ICIT-2017 

TitleExperimenting Capacitive Sensing Techniques for Structural Integrity Assessment

VenueHilton Toronto, 145 Richmond Street West, Toronto, Ontario, M5H 2L2, Canada

Time10:00 AM - 10:30 AM


ICTA-2016 

TitleAn Improved Tuning Control Algorithm Based on SVD for FID Signal

VenueTokyo University of Technology, 1404-1 Katakuramachi, Hachioji, Tokyo, Japan

Time9:00 AM - 9:30 AM


Reviewer


ConferenceIEEE International Conference on Industrial Technology (ICIT)

Journal: IEEE Transactions on Industrial Electronics

Journal: IEEE Transactions on Reliability

Journal: Measurement



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