Homayoon Alimoradi | Seismology | Young Scientist Award

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Mr. Homayoon Alimoradi | Seismology | Young Scientist Award

PhD student |  University of Tehran Iran

Homayoon Alimoradi, born in 1991 in Kermanshah, Iran, is a Ph.D. candidate in Seismology at the University of Tehran. He ranked 2nd in the Iranian Seismology Ph.D. entrance exam in 2021. He holds a Master’s in Geophysics and a Bachelor’s in Physics from Razi University. His research focuses on earthquake precursors, remote sensing, and seismic exploration. He has extensive experience in geophysical data analysis, programming in MATLAB and Python, and using specialized seismological software. His work includes field studies, satellite data analysis, and geophysical surveys, with multiple publications in high-impact journals and conferences.

Publication Profile

Scopus

🎓Education

Ph.D. in Seismology (2021-Present) – University of Tehran, focusing on earthquake precursors using satellite data in the Alpine-Himalayan seismic belt. M.Sc. in Geophysics (2017-2020) – Razi University, thesis on Earth’s magnetic field variation before and after earthquakes using swarm satellite data. B.Sc. in Physics (2012-2017) – Razi University, with a focus on geophysical and seismic studies.

💼Experience

Conducted seismic refraction, geo-electric studies, and downhole seismic analysis for metro and geotechnical projects in Tehran. Led GPR surveys for subsurface utility mapping, seismic noise measurement for power plants, and soil resistance studies. Specialized in MASW data processing, seismic network noise surveys, and geophysical data acquisition. Proficient in MATLAB, Python, and geophysical software like SeisImager, ReflexW, and GMT. Participated in various earthquake-related research and field projects across Iran.

🏆Awards and Honors

Ranked 2nd in the Iranian National Ph.D. Entrance Exam in Seismology (2021). Recipient of multiple research grants and scholarships for geophysical studies. Best Paper Presentation in leading Iranian geophysics and seismology conferences. Recognized for outstanding contributions to earthquake precursor research.

🔬Research Focus

Earthquake Precursors – Investigating pre-seismic anomalies using satellite data. Remote Sensing & Geophysics – Utilizing advanced imaging and geophysical techniques. Seismic Data Analysis – Processing and interpreting seismic and geoelectric data. Machine Learning in Seismology – Developing AI-driven predictive models for earthquake analysis. Geophysical Instrumentation – Expertise in GPR, seismic, and electrical resistance surveys.

Conclusion

Dr. Dongwook Kim’s outstanding academic credentials, substantial contributions to smart construction, and active role in shaping BIM standards make him a prime candidate for the Best Researcher Award. His continuous involvement in cutting-edge projects and technical committees demonstrates his leadership in the transformation of the civil engineering industry. With some focused attention on integrating newer technological advancements, particularly in AI, his research has the potential to drive significant innovation in the construction sector.

Publications

  1. Title: Foundations for an Operational Earthquake Prediction System
    Year: 2025
    Authors: Angelo de Santis, Gianfranco Cianchini, Loredana Perrone, Habib Rahimi, Homayoon Alimoradi

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