LIU JIANXIN | Planetary Sciences | Best Researcher Award

Mr. LIU JIANXIN | Planetary Sciences | Best Researcher Award

Professor at Central South University, China

Liu Jianxin is a distinguished second-level professor and doctoral supervisor at Central South University (CSU), China. Born in 1962 in Yueyang, China, he has dedicated his career to advancing geological exploration and applied geophysics. With over 40 years of experience, Liu has made significant contributions to resource detection, mineral exploration, and the development of advanced geophysical methodologies. He has published over 360 research papers, authored 25 books, and holds 32 patents, including three international PCT patents. His research has directly contributed to the discovery of critical mineral resources, alleviating mineral scarcity for industries and society. Liu has been instrumental in training future geoscientists and has led numerous national and provincial research projects. His exceptional achievements have earned him prestigious awards and recognitions, including national invention and science progress prizes. As a leader in academia, Liu continues to influence geophysical research, policy-making, and resource management, making him a pivotal figure in geological engineering.

Professional Profile

Education

Liu Jianxin’s academic journey began with a Bachelor’s degree in Geophysical Prospecting from the Central-South Institute of Mining and Metallurgy in 1983. He pursued advanced studies at Central South University (formerly Central South University of Technology), earning a Master’s degree in Applied Geophysics in 1990 and a Ph.D. in Geophysical Prospecting and Information Technology in 2006. His education laid a robust foundation for his career in geophysics and resource exploration. Liu’s extensive academic background reflects his deep commitment to mastering and advancing his field. His training in geophysical methodologies and information technologies enabled him to develop innovative exploration techniques, bridging theoretical knowledge with practical applications in mining and resource detection. This comprehensive academic preparation has positioned Liu as a leading expert and educator in geological engineering, fostering groundbreaking advancements in the discipline.

Professional Experience

Liu Jianxin has held numerous influential positions throughout his career. He has served as the Dean of the School of Information Physics Engineering and Vice Dean of the School of Geosciences and Info-Physics at CSU. He is currently the Chairman of the Professor Committee of the School of Geosciences and Info-Physics and Dean of the Geological Survey Institute at CSU. Beyond academia, Liu has played a significant role in national and regional organizations. He is Vice President of the Chinese Geophysical Society, a Member of the Expert Steering Group for China’s “National Strategic Action for Mineral Exploration and Breakthrough,” and Vice President of the Hunan Provincial Intellectuals Association. Liu has led over 100 research projects, including national initiatives like the National High-Tech R&D Program (863 Program). His leadership extends to academic organizations, policy-making, and industry collaborations, demonstrating his profound influence on geophysical exploration and resource management.

Research Interests

Liu Jianxin’s research interests center on geophysical exploration, resource detection, and geological engineering. He focuses on developing and applying advanced methodologies for detecting deeply buried mineral deposits. His expertise lies in multi-scale three-dimensional electromagnetic exploration, dual-frequency induced polarization, and pseudo-random electromagnetic techniques. These methods address challenges in deep resource exploration, such as interference and precision in detection. Liu’s research has practical applications, contributing to the discovery of critical resources in lead-zinc, silver, and phosphate mines across China. He is also interested in integrating geophysical methods with 3D visualization to enhance the accuracy and efficiency of mineral exploration. His innovative approaches bridge the gap between theory and practice, providing valuable solutions for mining industries and advancing geological science.

Research Skills

Liu Jianxin possesses a comprehensive skill set in geophysical exploration and data analysis. His expertise includes developing advanced electromagnetic and induced polarization methods for detecting deeply hidden mineral resources. Liu is proficient in designing geophysical instruments and integrating geophysical data with 3D visualization technologies. His ability to lead large-scale, multidisciplinary research projects reflects his organizational and analytical skills. Liu’s extensive experience in applied research enables him to bridge theoretical knowledge with practical solutions, making him a leader in solving complex geological challenges. His skills extend to mentoring and training researchers, fostering the next generation of geoscientists.

Awards and Honors

Liu Jianxin has received numerous prestigious awards, recognizing his exceptional contributions to geophysical exploration and geological engineering. He was awarded the Special Allowance of the State Council of China and was selected for the National Hundred, Thousand and Ten-Thousand Talent Project and the Program for New Century Excellent Talents by the Ministry of Education of China. His accolades include the Second Prize of National Invention and Second and Third Prizes of National Science and Technology Progress. Additionally, he has won 7 First Prizes and 5 Second Prizes at provincial and ministerial levels. These honors highlight his significant impact on the field, his innovative methodologies, and his leadership in advancing geological sciences.

Conclusion

Professor Liu Jianxin is a highly accomplished researcher whose contributions to geophysical exploration and mining are both innovative and impactful. His prolific output, leadership roles, and real-world impact position him as an ideal candidate for the Best Researcher Award. Strengthening global collaborations and expanding interdisciplinary applications could further augment his already outstanding profile. Overall, his achievements make him a strong contender for this prestigious recognition.

Publication Top Notes

  1. Azimuthal Prestack Seismic Inversion for Fracture Parameters Based on L1–2 Norm Regularization
  2. Deep Learning-Based Suppression of Strong Noise in GPR Data for Railway Subgrade Detection
  3. Divergence-Free: A Crucial Strategy to Speed Up the Convergence of a Multigrid Solver for 3D Natural Source Electromagnetic Modeling
    • Authors: Rongwen Guo, Min Yu, Yongfei Wang, Jianxin Liu, Akande Akintunde Abiodun, Dengkang Wang, Xinhao Chen
    • Year: 2024
    • DOI: 10.1109/TGRS.2024.3506739
  4. Efficient 3-D Gravity Data Inversion With Depth Weighting Function
    • Authors: Xulong Wang, Jian Li, Qianjiang Zhang, Dongdong Zhao, Jianxin Liu, Kun Li
    • Year: 2024
    • DOI: 10.1109/TGRS.2024.3493418
  5. P-Wave Amplitude Versus Offset and Azimuth and Low-Frequency Anisotropic Poro-Acoustoelasticity
  6. Structure-Guided Multiscale Impedance Inversion Based on Modified Total Variation Regularization
    • Authors: Hao Li, Yian Cui, Pu Wang, Youjun Guo, Yang Yuan, Pengfei Zhang, Jianxin Liu
    • Year: 2024
    • DOI: 10.1109/TGRS.2024.3491212
  7. Efficient Trans-Dimensional Bayesian Inversion of C-Response Data from Geomagnetic Observatory and Satellite Magnetic Data
    • Authors: Rongwen Guo, Shengqi Tian, Jianxin Liu, Yi-an Cui, Chuanghua Cao
    • Year: 2024
    • DOI: 10.3390/app142310944
  8. Efficient Large-Scale 3D Gravity Modeling Using a Fast Evaluate Kernel Matrix Combined with Compressed Matrix Techniques
  9. An Integrated Approach for Sewage Diversion: Case of the Huayuan Mine, Hunan Province, China
    • Authors: Kouao Laurent Kouadio, Jianxin Liu, Wenxiang Liu, Rong Liu, Zakaria Boukhalfa
    • Year: 2024
    • DOI: 10.1190/geo2023-0332.1
  10. Geophysical Field Data Interpolation Using Stochastic Partial Differential Equations for Gold Exploration in Dayaoshan, Guangxi, China
    • Authors: Zhenwei Guo, Xiangping Hu, Liu Jianxin, Chunming Liu, Jianping Xiao
    • Year: 2018
    • DOI: 10.3390/min9010014

Yan Zhen | Planetary Sciences | Best Researcher Award

Assoc Prof Dr. Yan Zhen | Planetary Sciences | Best Researcher Award

Research Associate at Southwest Petroleum University, China

Zhen Yan is an Associate Professor at Southwest Petroleum University, specializing in GIS spatio-temporal big data mining and artificial intelligence applications in oil and gas geology. He holds a BS in Computer Science and Technology from Shanxi Normal University and a Ph.D. in Cartography and Geographic Information Systems from Nanjing Normal University. His professional experience includes serving as a senior engineer at the Department of Natural Resources in China before transitioning to academia. Zhen has made significant contributions to the field through several high-impact publications, including studies on predictive modeling for well production and lithofacies identification. His research is characterized by a practical focus on engineering problems and innovative methodologies. Although he has a strong foundation in his field, expanding the impact of his research beyond oil and gas and increasing interdisciplinary collaborations could enhance his work’s broader relevance. Zhen Yan is a promising candidate for the Best Researcher Award.

Profile:

Education

Zhen Yan’s educational background is a testament to his commitment to excellence in the fields of computer science and geographical information science. He earned his Bachelor of Science degree in Computer Science and Technology from Shanxi Normal University in 2008, where he laid the foundation for his technical skills and understanding of computational principles. Building on this solid groundwork, he pursued a Ph.D. in Cartography and Geographic Information Systems at Nanjing Normal University, graduating in 2013. This advanced degree equipped him with specialized knowledge in spatial data analysis and geospatial technologies, which are crucial for addressing complex engineering challenges. Zhen’s academic journey not only reflects his dedication to mastering technical concepts but also highlights his ability to integrate multidisciplinary approaches to research, particularly in the context of oil and gas geology. His educational experiences have significantly shaped his research interests and professional development as an associate professor and researcher.

Professional Experiences 

Zhen Yan has cultivated a diverse professional background that bridges both academic and practical engineering fields. Beginning his career as a senior engineer at the Department of Natural Resources in China’s Topographic Survey Team 6 (2013-2017), he gained expertise in underground space analysis and natural resource management. This role sharpened his skills in applying geographical information systems (GIS) and big data analytics to real-world challenges. In 2017, Zhen transitioned to academia as an associate professor at Southwest Petroleum University, where he joined the School of Geosciences and Technology. Here, he expanded his focus to oil and gas geology, integrating artificial intelligence and spatio-temporal data mining into his research. His ongoing academic role allows him to blend theoretical research with practical engineering solutions, particularly within the petroleum industry. Zhen’s experience reflects a well-rounded approach to both solving engineering problems and advancing academic knowledge in GIS and AI-driven big data analytics.

Research Interests

Zhen Yan’s research interests lie at the intersection of geographic information science and artificial intelligence, particularly in the context of oil and gas geology. His work focuses on the application of GIS spatio-temporal big data mining techniques to analyze complex geological data, enhancing our understanding of subsurface conditions. Zhen is particularly interested in developing predictive models for well production and identifying lithofacies types using advanced algorithms, including temporal convolution networks and boosting techniques. His research also explores innovative methodologies for predicting sand body thickness and deep low-permeability sandstone reservoirs through machine learning approaches. By integrating big data analysis with geological research, Zhen aims to provide robust solutions to engineering challenges in the oil and gas sector, contributing to more efficient resource extraction and management. His interdisciplinary approach not only advances theoretical knowledge but also addresses practical issues faced by the industry.

Research Skills

Zhen Yan possesses a diverse set of research skills that significantly contribute to his expertise in the fields of computer science and geographical information systems. His proficiency in GIS spatio-temporal big data mining enables him to analyze complex datasets effectively, facilitating insights into oil and gas geology. Zhen is adept at employing artificial intelligence techniques, including machine learning algorithms, to enhance predictive modeling, as evidenced by his publications on well production prediction and lithofacies identification. His ability to utilize advanced computational tools, such as convolutional neural networks (CNN) and boosting algorithms, showcases his technical acumen. Furthermore, Zhen demonstrates strong problem-solving skills through innovative methodologies for predicting reservoir characteristics and sand body thickness. His collaborative approach to research fosters teamwork and knowledge sharing, enriching the research process. Overall, Zhen’s blend of analytical skills, technical expertise, and collaborative spirit positions him as a valuable contributor to his field.

Award and Recognition 

Zhen Yan has garnered significant recognition in the field of geosciences and technology through his innovative research and contributions. As an associate professor at Southwest Petroleum University, he has been instrumental in advancing methodologies in GIS spatio-temporal big data mining and artificial intelligence applications in oil and gas geology. His work has led to multiple publications in reputable journals, including notable studies on well production prediction and lithofacies identification, which have received considerable attention in the scientific community. Zhen’s research has not only enhanced predictive modeling in the oil and gas sector but has also paved the way for future studies in related fields. His expertise and collaborative efforts have earned him respect among peers and industry professionals alike, positioning him as a leading figure in his area of specialization. Zhen Yan’s achievements reflect his commitment to advancing scientific knowledge and addressing pressing engineering challenges.

Conclusion

Zhen Yan stands out as a strong candidate for the Best Researcher Award due to his innovative research, solid educational background, and impressive publication record. His work directly addresses critical issues in the oil and gas industry, leveraging cutting-edge technologies to improve predictions and analysis. By enhancing his outreach efforts and expanding the scope of his research, he can further solidify his impact on both academia and industry. Overall, Zhen’s contributions are significant, and with targeted improvements, he can elevate his research to new heights, making him a deserving nominee for the award.

Publication Top Notes
  1. Prediction of deep low permeability sandstone seismic reservoir based on CBAM-CNN
    Authors: Zhen, Y., Zhang, A., Zhao, X., Zhao, Z., Yang, C.
    Year: 2024
    Citations: 0
  2. Identifying lithofacies types by boosting algorithm and resampling technique: a case study of deep-water submarine fans in an oil field in West Africa
    Authors: Zhen, Y., Xiao, Y., Zhao, X., Kang, J., Liu, L.
    Year: 2023
    Citations: 0
  3. A Novel Error Criterion of Fundamental Matrix Based on Principal Component Analysis
    Authors: Bian, Y., Fang, S., Zhou, Y., Zhen, Y., Chu, Y.
    Year: 2022
    Citations: 0
  4. Temporal convolution network based on attention mechanism for well production prediction
    Authors: Zhen, Y., Fang, J., Zhao, X., Ge, J., Xiao, Y.
    Year: 2022
    Citations: 22
  5. An Optimization of Statistical Index Method Based on Gaussian Process Regression and GeoDetector, for Higher Accurate Landslide Susceptibility Modeling
    Authors: Cheng, C., Yang, Y., Zhong, F., Song, C., Zhen, Y.
    Year: 2022
    Citations: 4
  6. Relationship between habitat quality change and the expansion of Spartina alterniflora in the coastal area: Taking Yancheng National Nature Reserve in Jiangsu Province as an example
    Authors: Zhang, H., Zhen, Y., Wu, F., Li, Y., Zhang, Y.
    Year: 2020
    Citations: 9
  7. Spatial distribution characteristics of soil organic matter and nitrogen under natural conditions in Yancheng coastal wetlands
    Authors: Xu, Y., Zhen, Y., Han, S., Zhang, H.-B.
    Year: 2018
    Citations: 2
  8. Uncertainty measurement model of three-dimensional polygon
    Authors: Bian, Y., Liu, X., Zhen, Y.
    Year: 2015
    Citations: 1
  9. Precise fundamental matrix estimation based on inlier distribution constraint
    Authors: Zhen, Y., Liu, X., Wang, M.
    Year: 2013
    Citations: 0
  10. Fundamental matrix estimation based on inlier distributions constraint
    Authors: Zhen, Y., Liu, X., Wang, M.
    Year: 2013
    Citations: 1