Dr. Lizheng Deng, Tsinghua University, China
Dr. Lizheng Deng, born in September 1994 in Anhui Province, China, is a postdoctoral researcher at the School of Safety Science, Institute of Public Safety Research, Tsinghua University in Beijing. He holds a Ph.D. in Safety Science and Engineering from Tsinghua University, where his dissertation focused on landslide subsurface deformation behavior using acoustic emission (AE) monitoring under the mentorship of Professor Hongyong Yuan. His academic journey also includes visiting research stints at Loughborough University in the UK and Montanuniversitaet Leoben in Austria. Dr. Deng’s research centers on geotechnical monitoring, particularly leveraging acoustic emission technologies and artificial intelligence to assess and predict subsurface deformation in geological settings. His work during his Ph.D. led to the development of an innovative AE waveguide array, now employed in landslide monitoring projects across multiple provinces in China. In his postdoctoral research, he continues to explore the dynamics of granular material–metal structure interactions and the associated AE mechanisms, with the support of the Beijing Natural Science Foundation and China Postdoctoral Science Foundation.
Professional Profile:
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Summary of Suitability for the Research for Best Researcher Award
Dr. Lizheng Deng stands out as a highly suitable candidate for the Research for Best Researcher Award based on his impressive academic and research trajectory, international collaborations, and impactful contributions to geotechnical monitoring using Acoustic Emission (AE) and Artificial Intelligence (AI). With a Ph.D. from Tsinghua University and postdoctoral research at the same prestigious institution, Dr. Deng has made significant advancements in landslide subsurface deformation behavior monitoring, a critical area for disaster risk reduction. His innovations, such as the AE array and AI-integrated early warning models, are not only academically recognized—published in top-tier journals like Engineering Geology and Landslides—but also applied nationwide, directly influencing public safety via China’s GeoCloud monitoring system. Funded by leading scientific foundations and supported by multiple government ministries, Dr. Deng’s research is both cutting-edge and socially impactful, embodying the excellence and real-world application expected of a recipient of this award.
🎓 Education
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PhD in Safety Science and Engineering (09/2017 – 06/2022)
Tsinghua University, Beijing, China 🇨🇳
Dissertation: “Research on Landslide Subsurface Deformation Behaviour Using Acoustic Emission Monitoring”
👨🏫 Supervisor: Prof. Hongyong Yuan (Chang Jiang Scholars)
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Visiting PhD Student (02/2020 – 08/2020)
Loughborough University, UK 🇬🇧
👨🏫 Supervisors: Prof. Neil Dixon, Alister Smith
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B.E. in Safety Engineering (09/2013 – 06/2017)
China University of Mining and Technology, Beijing
Thesis: Roof control methods in hard rock mining >700m
👨🏫 Supervisor: Prof. Yueping Qin, Prof. Nikolaus A. Sifferlinger
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Visiting Student (02/2017 – 05/2017)
Montanuniversitaet Leoben, Austria 🇦🇹
👨🏫 Supervisor: Prof. Nikolaus A. Sifferlinger
💼 Work Experience
🏆 Achievements & Contributions
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🔬 Innovated AE Array Monitoring Technology
Used in landslide early warning systems across 20+ sites in 8 provinces in China.
👉 Integrated with AI for landslide deformation modeling and risk prediction.
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🛠 Field Implementation & Tech Adoption
AE monitoring tech adopted by:
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📚 Publications in top journals
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Engineering Geology
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Landslides
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Measurement
🥇 Awards & Honors
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🧾 “Certificate of Universal Instrumentation for Geological Hazard Monitoring” – Ministry of Natural Resources, China
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🙌 Letter of Appreciation – Recognizing real-world impact of his monitoring tech
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💰 Funded by:
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Beijing Natural Science Foundation
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China Postdoctoral Science Foundation
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Ministry of Industry and Information Technology of China
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Ministry of Natural Resources of China
Publication Top Notes:
Spatio-Temporal Deformation Prediction of Large Landslides in the Three Gorges Reservoir Area Based on Time-Series Graph Convolutional Network Model
Acoustic emission behavior generated from active waveguide during shearing process
Noise Cancellation Method Based on TVF-EMD with Bayesian Parameter Optimization
Automatic classification of landslide kinematics using acoustic emission measurements and machine learning
Machine learning prediction of landslide deformation behaviour using acoustic emission and rainfall measurements
Experimental Investigation on Integrated Subsurface Monitoring of Soil Slope Using Acoustic Emission and Mechanical Measurement
Correlation between Acoustic Emission Behaviour and Dynamics Model during Three-Stage Deformation Process of Soil Landslide
On Image Fusion of Ground Surface Vibration for Mapping and Locating Underground Pipeline Leakage: An Experimental Investigation