Liu Yong, professor, doctoral supervisor. 2013-2014: Postdoctoral at University of Connecticut; 2008-2011: PhD at China University of Geosciences; 2001-2004: Master degree with honors from University of Wollongong, cooperative education program of Huazhong University of Science and Technology - University of Wollongong. He has presided over two programs supported by National Natural Science Foundation of China, one sub-project of the major program supported by the National Natural Science Foundation of China, several major national engineering programs, and one open fund for key laboratories of the Ministry of Education. His main research fields are computational intelligence algorithm, information fusion and information assimilation, and landslide information processing, etc. He has published many academic papers in important academic journals and conferences both at home and abroad, published two monographs, and applied for several invention patents.
Contact information:
Email: cugly@qq.com
Office: Room 519, No. 2 Teaching Building
I. Main education and work experiences:
2024/01-present: Professor and doctoral supervisor at School of Mechanical Engineering and Electronic Information, China University of Geosciences (Wuhan)
2011/11-2023/12: Associate professor at School of Mechanical Engineering and Electronic Information, China University of Geosciences (Wuhan)
2013/10-2014/10: Postdoctoral at Department of Civil and Environmental Engineering, University of Connecticut
2008/09-2011/06: Doctor at Faculty of Engineering, China University of Geosciences (Wuhan)
2004/07-2011/12: Lecturer at School of Mechanical Engineering and Electronic Information, China University of Geosciences (Wuhan)
2003/09-2004/06: Master at School of Computing and Information Technology, University of Wollongong
II. Main research fields:
1. Artificial intelligence. Research on deep learning, intelligent optimization algorithm and improved algorithm.
Including particle swarm optimization algorithm, ant colony algorithm, artificial neural network, deep learning network and other basic algorithms and improved algorithms, as well as the application of these algorithms in information processing and feature analysis, including the applications in intelligent geological information processing and intelligent Internet of things.
2. Virtual reality and reality enhancement. Research on virtual reality and mixed reality
Including the modeling of VR helmet and VR glove data modeling, feature analysis and extraction of data, system design of Unreal and Unity software, and the research on object motion trajectory and posture.
3. Intelligent information processing. Systematic research on information fusion, information assimilation and other intelligent information processing methods
Including multi-sensor, multi-parameter information dimension reduction, information features analysis, high-dimensional data feature-based modeling, high-dimensional data prediction, similarity comparison of high-dimensional data, information interpolation of high-dimensional data, etc
III. Research programs in recent years as the principal investigator:
1. General Program of National Natural Science Foundation of China: Research on the intelligent assimilation method of reservoir landslide based on the expansion of multi-scale convolution transfer model, 2018/01-2021/12, RMB 690,000Yuan
2. Youth Program of National Natural Science Foundation of China: Research on the information fusion method of multi-parameter flow data in the prediction of soft rock bedding landslide in Badong Group, 2014/01-2016/12, RMB 350,000Yuan
3. Major project of National Natural Science Foundation of China: 42090054, Mechanism and criteria for the initiation of dynamic water driven landslides, 2021/01/01-2025/12/31, RMB 3,550,000Yuan, under study, principal investigator of a sub-project
4. Enterprise sponsored program of the key project of State Grid: Research on the interactive simulation model of three-dimensional virtual reality environment for safety management and control of measurement work, 2019/01-2021/12, RMB 1,000,000Yuan
5. Enterprise sponsored program of state key project: Advance geological prediction and bottom detection of Chenjia Tunnel and Shimazhai Tunnel, 2015/06-2020/12, RMB 1,000,000Yuan
6. Enterprise sponsored program of the key project of State Grid: Research on the design of automation module and intelligent information processing of electric power testing instrument, 2019/01-2021/12, RMB 450,000Yuan
7. Enterprise sponsored program of State Grid: Research on load signal and error effects of low-voltage current transformers for measurement under typical operating conditions, 2020/11-2020/12, RMB 100,000Yuan
Notes: The programs listed above are those I have presided over in recent years, and the program which I have participated in and historical programs are not listed due to too many items. At present, the research group is engaged in the programs supported by national foundation and enterprises, so we have a good focus on scientific research and enterprise service. The research group keeps sound cooperation with large enterprises and institutions as well as Internet enterprises in the industry, has sufficient research funds, and is thus able to offer competitive achievement awards and internship employment opportunities.
IV. Scientific research achievements:
Published academic papers:
(1) Yong Liu, Jingjing Long, Changdong Li, Weiwen Zhan. Physics-informed data assimilation model for displacement prediction of hydrodynamic pressure-driven landslide[J]. Computers and Geotechnics, 2024,1(67): 81-103. DOI: 106085.202401 (T1) first author
(2) Liu Y., Xu C., Huang B., et al. Landslide displacement prediction based on multi-source data fusion and sensitivity states[J]. Engineering Geology, 2020. DOI: 10.1016/j.enggeo.2020.105608 (T1) first author
(3) Zhong L., Ge M.F., Zhang S.Z., Liu Y.(*). Rate Aware Fuzzy Clustering and Stable Sensor Association for Load Balancing in WSNs[J]. IEEE Internet of Things Journal, 2021. DOI: 10.1109/JIOT.2021.3098352 (T1) corresponding author
(4) Long J.J., Li C.D., Liu Y.(*), et al. A Multi-Feature Fusion Transfer Learning Method for Displacement Prediction of Rainfall Reservoir-Induced Landslide with Step-Like Deformation Characteristics[J]. Engineering Geology, 2021. DOI: 10.1016/j.enggeo.2021.106494 (T1) corresponding author
(5) Zhong L., Zhang S.Z., Yidu Z., Guang C., Liu Y.(*). Joint acquisition time design and sensor association for wireless sensor networks in microgrids Authors[J]. Energies, 2021.DOI:10.3390/en14227756 (T2) corresponding author
(6) Wei H., Ma L., Liu Y.(*), et al. Combining Multiple Classifiers for Domain Adaptation of Remote Sensing Image Classification[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021.DOI: 10.1109/JSTARS.2021.3049527 (T2) corresponding author
(7) Li C.D., Long J.J., Liu Y.(*), et al. Mechanism analysis and partition characteristics of a recent highway landslide in Southwest China based on a 3D multi-point deformation monitoring system[J]. landslides, 2021, DOI: 10.1007/s10346-021-01698-2 (T2) corresponding author
(8) Long J.J., Yong L., Li C.D., et al. A novel model for regional susceptibility mapping of rainfall-reservoir induced landslides in Jurassic slide-prone strata of western Hubei Province, Three Gorges Reservoir area[J]. Stochastic Environmental Research and Risk Assessment,2020. DOI: 10.1007/s00477-020-01892-z 23456789().,-volV)(0123456 (T2) student as first author
(9) He Fangqiuzi, Liu Y.(*), Zhan W.W., et al. Manual Operation Evaluation Based on Vectorized Spatio-Temporal Graph Convolutional for Virtual Reality Training in Smart Grid[J]. Energies, 2022. DOI: DOI:10.3390/en15062071 (T2) corresponding author
(10) Liu Y., Zhan W.W., Li Y., et al.. Grid-Related Fine Action Segmentation Based on an STCNN-MCM Joint Algorithm during Smart Grid Training[J]. Energies,2023. DOI:10.3390/en16031455 (T2) first author
(11) Liu Y., Xu Q.J., Li X.R., et al. A Small-Sample Borehole Fluvial Facies Identification Method Using Generative Adversarial Networks in the Context of Gas-Fired Power Generation, with the Hangjinqi Gas Field in the Ordos Basin as an Example[J]. Energies 2023. DOI:10.3390/en16031361 (T2) first author
Monographs:
(1) Yong Liu, Hongming Yu, Li Ma, Modern Information Processing Method for Landslide Monitoring Data, Changjiang Press, 185000, 2017/03/01
(2) Yong Liu, Hongming Yu, Ping Zhong, Le Tang, Pengyu Chen, Computational Intelligence Methods for Landslide Prediction, China University of Geosciences Press, 182000, 2012/12/01
Invention Patents:
(1) A method and a device for monitoring the transition of wading landslide - 201610497751.8
(2) A method for analyzing the time-varying law of landslide stability - 201611112255.2
(3) A method for monitoring and analyzing the landslide motion patterns based on information fusion - 201611155056.X
(4) A method for evaluating the deformation similarity of landslide based on motion angle difference - 201611270807.2
(5) A four-dimensional interpolation data processing method, device and storage device - 201710632818.9
(6) A three-dimensional interpolation modeling method, device and storage device - 201710676502.X
(7) A method for dynamic response analysis of landslides with multiple affecting factors - 201711042714.9
(8) Landslide monitoring points zoning method, device and storage device based on block chain framework - 201810928872.2
(9) A method and system for matching the landslide displacement similarity based on movement angle difference - 201810981007.4
Software copyright:
(1) Yong Liu, Zhe Chen, Dynamic representation system of rainfall-induced landslides, software copyright registration No.: 2017SR233217
(2) Yong Liu, Baodan Hu, Interpolation based landslide 3D model representation software V1.0, software copyright registration No.: 2018SR977562
(3) Changdong Li, Yong Liu, et al. Software for analyzing the response mechanism of storm-induced landslide deformation based on mutual information quantity, software copyright registration No.: 2021SR0364855
Teaching program:
2017 High-quality course development program for postgraduates: Internet of things and intelligent network communication. 2017/06-2019/06
V. Students in recent five years:
Grade 2014: Dan Liu (Wuhan Metro), Fengbo Liu (CAICT), Yani Guo (ISOFTSTONE), KERRY RAJIV (overseas student, returned), MUSTAFE MOHAMED (overseas student, returned), Xiaodan Zhang (on-the-job, Xi’an No. 1 People’s Hospital), Qingyun Chen (on-the-job)
Grade 2015: Zhimeng Qin (CAICT), Shuai Feng (VIVO), Zhimin Dong (H3C), Junda Wei (FiberHome), Gen Li, (FiberHome), Jie Xu (on-the-job, Wuhan Business University), Yefan Wang (on-the-job).
Grade 2016: Zhe Chen (VIVO), AL-TAWILI FAHD (overseas student, returned)
Grade 2017: Baodan Hu (China Merchants Bank), Zhao Wu (FiberHome), Jingkun Jin (Beijing Shengda)
Grade 2018: Chang Xu (at school, national scholarship winner)
Grade 2020: Pengfei Feng (studying for a doctorate), Kai Ren (BYD), Jiongwei Zhao (BYD)
Grade 2021: Xingrui Li (Wuhan Municipal Education Bureau), Jingkai Guo (FiberHome), Wenhao Chen (Xiaomi), Weiwen Zhan (China Railway Wuhan Group)
Notes:
1. All students have published high-quality papers indexed by SCI and EI and have received well training on professional knowledge and competence during their studying for master degree.
2. All students have well internship experience, including banking system (Bank of Zhengzhou), Internet industry (Huawei, SenseTime, VIVO, Sogou Music), network security system (Hikvision), State Grid System (State Grid), etc. In addition to getting higher income from scientific research grants, they can also adapt to the enterprise environment and learn about the work condition in the industry. They will have a deeper and comprehensive understanding of their own ability and enterprise requirements at the time of finding a job, which can also greatly enhance their employment advantages.
3. In recent years, all graduates have been employed by Wuhan Metro, Zhengzhou Telecom Research and Design Institute, Shengqu Games, VIVO, FiberHome, H3C, China Merchants Bank, ISOFTSTONE and other enterprises and public institutions, which have been listed after the student’s name. I believe that, in the next two decades, artificial intelligence, intelligent information processing and virtual reality will provide great advantages and competitiveness in further study and employment. After graduation, all the students of our team can enter scientific research institutes, large state-owned enterprises and high-paid Internet enterprises.
VI. Supervisor’s wishes:
When we study the performance of optimization algorithm, a very important criterion is whether the algorithm will fall into the local optimum and cannot jump out of it. Just like that, in the process of growing up, we tend to fall into our own comfort zone and miss our global optimization. In fact, each of us has the desire to jump out of the comfort zone and realize our life ideals!
Our team has good preliminary research, complete data and resources, and abundant funds. In our team, you are not required to have a deep foundation or a brilliant mind; as long as you work hard, you will have a clear research direction. In your three-year postgraduate career, I hope to encourage and accompany you as a friend, and spur and inspire you as a teacher. I hope you will succeed in your studies and move forward to your overall optimization.
I would like to recruit one doctoral student and 3-5 postgraduate students every year, and I look forward to your joining. In case of any confusion, welcome to discussing with me.
