Yunhe Liu | Geophysics| Best Researcher Award

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Dr. Yunhe Liu | Geophysics| Best Researcher Award

Professor at Jilin University, China

Yunhe Liu, Ph.D., is a renowned Geophysicist currently serving as a professor and Ph.D. supervisor at Jilin University’s College of GeoExploration Science and Technology. His academic journey began with a B.Sc. in Applied Geophysics (2005), followed by an M.Sc. and Ph.D. in Exploration Geophysics (2011). He has held various academic roles, including visiting scholar positions at the University of Queensland and Memorial University of Newfoundland. His research focuses on electromagnetic methods, 3D inversion modeling, and geophysical exploration technologies.

Publication Profile

Scopus

Scholar

Education🎓

Ph.D. in Exploration Geophysics, Jilin University, 2011. M.Sc. in Exploration Geophysics, Jilin University, 2008. B.Sc. in Applied Geophysics, Jilin University, 2005

Experience💼

Yunhe Liu has extensive academic experience, currently a professor at Jilin University since 2020. He also serves as a visiting scholar at the University of Queensland, Australia. Previously, Liu worked as an associate professor, lecturer, and postdoctoral fellow at Jilin University. His roles have consistently emphasized geophysical research and education, and he has supervised multiple doctoral students since 2019. Liu’s work has significantly impacted the advancement of geophysical technologies and exploration methodologies.

Awards and Honors🏆

2023 Reviewer of the Year (Geophysics). 2020 China Geophysical Society Science and Technology Progress Award (Second Prize). 2018 SEG “Bright Spot Paper” Award. 2018 Chen Zongqi Outstanding Geophysics Paper Prize. 7th Liu Guangding Youth Geophysics Science and Technology Award

Research Focus🔬

Liu’s research primarily centers on geophysical exploration technologies, with an emphasis on 3D inversion modeling, electromagnetic methods, and the integration of advanced algorithms. His ongoing projects include developing probabilistic 3D anisotropic magnetotelluric inversion and working on space-based electromagnetic detection algorithms. He is also involved in several significant national programs related to marine exploration and geophysical data analysis. His work aims to enhance the precision and efficiency of geophysical exploration.

Conclusion

Dr. Yunhe Liu exemplifies the qualities of an outstanding researcher with deep academic expertise and a strong track record of leadership in high-impact projects. His ability to lead large-scale research initiatives, coupled with his global collaborations, makes him a prime candidate for the Best Researcher Award. Continued expansion into multidisciplinary research and broader engagement could further elevate his academic profile, making his contributions even more impactful.

Publications:

  1. Weighted goal-oriented adaptive finite-element for 3D transient EM modeling
    • Year: 2019
    • Authors: Y. Qi, X. Li, C. Yin, Z. Qi, J. Zhou, Y. Liu, B. Zhang

 

  1. Three-dimensional controlled source electromagnetic inversion using non-linear conjugate gradients
    • Year: 2012
    • Authors: W. Ai-Hua, L. Yun-He, J. Ding-Yu, L. Xiang-Dong, Y. Chang-Chun

 

  1. 三维可控源电磁法非线性共轭梯度反演研究 [Doctoral Thesis]
    • Year: 2011
    • Authors: 刘云鹤

 

  1. A fast 3-D inversion for airborne EM data using pre-conditioned stochastic gradient descent
    • Year: 2023
    • Authors: X. Ren, M. Lai, L. Wang, C. Yin, Y. Liu, Y. Su, B. Zhang, F. Ben, W. Huang

 

  1. Controlled-source electromagnetic modeling using a versatile secondary electric-field formulation and efficient multigrid-based preconditioner
    • Year: 2023
    • Authors: C. Qiu, Y. Liu, X. Ren, H. Chen, T. Yan

 

  1. 3-D forward modeling of transient EM field in rough media using implicit time-domain finite-element method
    • Year: 2022
    • Authors: Y. Liu, L. Wang, C. Yin, X. Ren, B. Zhang, Y. Su, Z. Rong, X. Ma

 

  1. GEM3D: a 3D inversion code for geophysical electromagnetic data based on unstructured tetrahedron grid
    • Year: 2019
    • Authors: Y. Liu, J. Zhang, C. Yin, C. Qiu, B. Zhang, X. Ren, Q. Wang

 

  1. 3D MT inversion based on model space compression
    • Year: 2019
    • Authors: Q. Wang, Y.H. Liu, C.C. Yin, J.F. Li, J. Zhang

 

  1. 3D Inversion of Semi-Airborne Transient Electromagnetic Data Based on Decoupled Mesh
    • Year: 2024
    • Authors: Z. Hui, X. Wang, C. Yin, Y. Liu

 

  1. 3D inversion of time-domain airborne EM data for IP parameters
    • Year: 2023
    • Authors: M. KaiFeng, Y. ChangChun, L. YunHe, S. SiYuan, X. Bin

 

Wang Jinlin| Geoscience | Best Innovation Award

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Prof. Dr. Wang Jinlin| Geoscience | Best Innovation Award

Prof. Dr at Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, China

Wang Jinlin is a Research Professor at the Institute of Space Applications Engineering and Technology, Chinese Academy of Sciences. With expertise in remote sensing geology, mathematical geology, hyperspectral applications, and GIS technology, his work significantly impacts resource exploration and geological analysis. He has contributed extensively to understanding and mapping mineral resources and developing advanced geospatial technologies.

Profile

Scopus

🎓 Education

Ph.D. in Cartography and Geographic Information System from Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences (2004-2010, supervised by Chen Xi). Bachelor’s in Resource Exploration Engineering from China University of Geosciences, Wuhan (1998-2002, supervised by Zhou Zonggui).

💼 Experience

Currently, Research Professor at the Institute of Space Applications Engineering and Technology, CAS (since 2023). Previously, Senior Engineer at Xinjiang Institute of Ecology and Geography, CAS (2020-2023), and Assistant Research Professor (2010-2015). Also served as a Visiting Scholar at Saint Louis University in 2011.

🏆 Awards & Honors

Received Science and Technology Progress awards from Xinjiang Uygur Autonomous Region People’s Government for projects on geological big data and tourism tech integration (2017). Holds patents in geological and spatial technology, including topological sorting of stratigraphic sequences (2021), and co-developed an award-winning dynamic platform for aero-magnetic surveys.

🔬 Research Focus

Specializes in remote sensing geology, hyperspectral imaging for mineral detection, and GIS for resource management. His research advances methods for metal estimation in rocks, hyperspectral data application, and innovative geological modeling and management systems.

Publications Top Notes

  • Pd(II)/Pd(IV) Redox Shuttle for Kesterite Solar Cells
    Authors: Wang, J., Shi, J., Yin, K., … Chen, S., Meng, Q.
    Journal: Nature Communications, 2024, 15(1), 4344
    This open-access article explores a Pd(II)/Pd(IV) redox shuttle method to reduce vacancy defects in kesterite solar cells, enhancing efficiency.

 

  • Multinary Alloying in Kesterite Solar Cells
    Authors: Shi, J., Wang, J., Meng, F., … Li, D., Meng, Q.
    Journal: Nature Energy, 2024, 9(9), 1095–1104
    The study discusses alloying to aid cation exchange and minimize defects in kesterite solar cells, achieving above 14% certified efficiency.

 

  • Lithium Content Estimation in Rock Debris via Spectral Feature Coefficients
    Authors: Jiang, G., Chen, X., Zhou, K., … Zhou, S., Bai, Y.
    Journal: Ore Geology Reviews, 2024, 171, 106167
    This paper focuses on a spectral feature-based method to estimate lithium content in rock samples, relevant for geochemical studies.

 

  • Impact of Band Optimization on Hyperspectral Metal Element Inversion Models
    Authors: Ma, X., Wang, J., Zhou, K., … De Maeyer, P., Van de Voorde, T.
    Journal: International Journal of Applied Earth Observation and Geoinformation, 2024, 132, 104011
    A quantitative evaluation of band optimization techniques to improve accuracy in metal element inversion models using hyperspectral data.

 

  • Inversion of Feldspar Content in Granite Using Hyperspectral Indices
    Authors: Wu, M., Jin, J., Wang, J., Wang, Q.
    Journal: Acta Geologica Sinica, 2024, 98(1), 314–323
    This research employs multi-angular hyperspectral indices to analyze and quantify feldspar content in granite.