![Peidong Shi](https://profiles-cardiff.imgix.net/attachments/7187?w=200&h=200&auto=format&crop=faces&fit=crop&q=90")
Dr Peidong Shi
(he/him)
Lecturer in Geophysics
- Available for postgraduate supervision
Overview
My research bridges geophysics, machine learning, and earthquake science, addressing challenges such as induced seismicity, sustainable energy solutions, and real-time seismic monitoring. With research experience across various institutes at ETH Zurich, ISTerre, and Leeds University, I am dedicated to research integrating AI, data science, digital twins, and high-performance computing to investigate Earth’s dynamic processes, with a focus on earthquake physics, geo-hazards, and renewable geo-energy solutions. My research goal is to advance our understanding of earthquake physical processes for seismic hazard mitigation and geo-energy project optimization. Through research and international collaborations, I’m passionate about driving impactful scientific discoveries and inspiring the next generation of researchers. Explore my research, projects, and publications to learn how we can collaborate towards a more resilient and sustainable future.
Publication
2025
- He, Y. et al. 2025. Experimental observation of moduli dispersion and attenuation at seismic frequencies in saturated tight rock: effect of microstructure and fluid viscosity. Geophysical Journal International 240, pp. 1308–1330. (10.1093/gji/ggae442)
2024
- Shi, P. et al. 2024. From labquakes to megathrusts: scaling deep learning based pickers over 15 orders of magnitude. Journal of Geophysical Research: Machine Learning and Computation 11(4), article number: e2024JH000220. (10.1029/2024JH000220)
- He, Y. -., Wang, S. X., Tang, G. Y., Dong, C. H., Sun, C., Yuan, S. Y. and Shi, P. D. 2024. Experimental investigation of pore-filling substitution effect on frequency-dependent elastic moduli of Berea sandstone. Geophysical Journal International 238(2), pp. 902–921. (10.1093/gji/ggae195)
- He, Y. et al. 2024. Laboratory experiments and theoretical study of pressure and fluid influences on acoustic response in tight rocks with pore microstructure. Geophysical Prospecting 72(5), pp. 1896-1918. (10.1111/1365-2478.13466)
- Finger, C., Tuinstra, K., Niemz, P., Shi, P., Ermert, L. and Lanza, F. 2024. Spatio-temporal evolution of hypocenters and moment tensors derived from time-reverse imaging. Presented at: EGU General Assembly 2024, Vienna, Austria, 14-19 April 2024. , (10.5194/egusphere-egu24-14828)
- Shi, P., Schultz, R., Lanza, F., Scarabello, L., Ermert, L. and Weimer, S. 2024. Machine learning based real-time microseismic monitoring and stimulated fracture characterization at the Utah FORGE Geothermal site. Presented at: EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024. , (10.5194/egusphere-egu24-15621)
- Parastatidis, E., Pytharouli, S., Stankovic, L., Stankovic, V., Shi, P. and Hildyard, M. W. 2024. Multichannel coherence migration grid search (MCMgs) in locating microseismic events recorded by a surface array. Geophysical Journal International 236(2), pp. 1042–1052. (10.1093/gji/ggad465)
- Obermann Anne, A., Goertz-Allmann, B., Sanchez-Pastor, P., Shi, P., Wu, S. and Hjórleifsdóttir, V. 2024. High-resolution seismic methods for geothermal exploration and monitoring across the Hengill volcanic area. Presented at: EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024. , (10.5194/egusphere-egu24-21112)
2023
- Mohammadigheymasi, H. et al. 2023. IPIML: A deep-scan earthquake detection and location workflow Integrating Pair-Input deep learning model and Migration Location method. IEEE Transactions on Geoscience and Remote Sensing 61 (10.1109/tgrs.2023.3293914)
- He, Y. et al. 2023. A physical modelling study of waveform amplification effects of reservoir heterogeneity on time‐lapse seismic attribute analysis. Geophysical Prospecting 71(2), pp. 206-226. (10.1111/1365-2478.13298)
- Yan, B., Ji, Y. and Shi, P. 2023. Frequency-dependent inversion based on spherical-wave reflection coefficient in elastic medium: Theory and methodology. Journal of Applied Geophysics 209, article number: 104908. (10.1016/j.jappgeo.2022.104908)
- Ermert, L., Lanza, F., Ciardo, F., Shi, P., Afanasiev, M. and Wiemer, S. 2023. Modeling the waveforms of induced seismicity sequences with application to Utah FORGE. Presented at: EGU General Assembly 2023, Vienna, Austria, 23 - 28 April 2023. , (10.5194/egusphere-egu23-11883)
- De solda, M., Grigoli, F., Shi, P., Lanza, F. and Wiemer, S. 2023. A deep learning-based workflow for microseismic event detection. Presented at: EGU General Assembly 2023, Vienna, Austria, 23 - 28 April 2023. , (10.5194/egusphere-egu23-1638)
- Shi, P., Lanza, F., Grigoli, F. and Wiemer, S. 2023. Near-real-time microseismic monitoring with machine-learning and waveform back-projection at the Utah FORGE geothermal site. Presented at: EGU General Assembly 2023, Vienna, Austria, 23 - 28 April 2023. , (10.5194/egusphere-egu23-13227)
- Nakata, N. et al. 2023. Elastic Characterization at Utah FORGE: P-wave Tomography and VSP Subsurface Imaging. Presented at: 48th Workshop on Geothermal Reservoir Engineering, California, USA, 6-8 February 2023Proceedings 48th Workshop on Geothermal Reservoir Engineering.
- Mohammadigheymasi, H., Tavakolizadeh, N., Shi, P., Xiao, Z., Mousavi, S. M. and Fernandes, R. 2023. An automated earthquake detection algorithm by combining pair-input deep learning and migration location methods. Presented at: EGU General Assembly 2023, Vienna, Austria, 23 - 28 April 2023. , (10.5194/egusphere-egu23-15180)
2022
- Shi, P., Grigoli, F., Lanza, F., Beroza, G. C., Scarabello, L. and Wiemer, S. 2022. MALMI: An automated earthquake detection and location workflow based on machine learning and waveform migration. Seismological Research Letters 93(5), pp. 2467-2483. (10.1785/0220220071)
- Obermann, A. et al. 2022. Combined large-N seismic arrays and DAS fiber optic cables across the Hengill geothermal field, Iceland. Seismological Research Letters 93(5), pp. 2498-2514. (10.1785/0220220073)
- Ermert, L., Lanza, F., Shi, P., Tuinstra, K. and Wiemer, S. 2022. Modeling induced micro-earthquakes for an experimental enhanced geothermal system site. Presented at: 20th Swiss Geoscience Meeting 2022, Lausanne, Switzerland, 18-20 November 2022.
- Shi, P., Grigoli, F., Lanza, F. and Wiemer, S. 2022. MALMI: towards combining machine learning and waveform migration for fully automated earthquake detection and location. Presented at: EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022. Copernicus {GmbH}, (10.5194/egusphere-egu22-6087)
2021
- Shi, P., Seydoux, L. and Poli, P. 2021. Unsupervised learning of seismic wavefield features: clustering continuous array seismic data during the 2009 L'Aquila earthquake. Journal of Geophysical Research: Solid Earth 126(1), article number: e2020JB020506. (10.1029/2020JB020506)
- Parastatidis, E., Pytharouli, S., Stankovic, L., Stankovic, V. and Shi, P. 2021. Minimising the computational time of a waveform based location algorithm. Presented at: EGU General Assembly (online) 2021, Online, 19 - 30 April 2021. , (10.5194/egusphere-egu21-15664)
- Shi, P. 2021. Towards real-time monitoring of induced microseismicity in enhanced geothermal systems. Presented at: 19th Swiss Geoscience Meeting, Geneva, Switzerland, 19-20 November 2021. pp. 19-19.
2020
- Li, L. et al. 2020. Recent advances and challenges of waveform‐based seismic location methods at multiple scales. Reviews of Geophysics 58(1), article number: e2019RG000667. (10.1029/2019RG000667)
- Yuan, S., Wei, W., Wang, D., Shi, P. and Wang, S. 2020. Goal-oriented inversion-based NMO correction using a Convex l 2,1 -norm. IEEE Geoscience and Remote Sensing Letters 17(1), pp. 162-166. (10.1109/LGRS.2019.2915520)
- Shi, P., Seydoux, L. and Poli, P. 2020. Direct fault states assessment from wavefield properties: application to the 2009 L'Aquila earthquake. Presented at: EGU General Assembly 2020, Online, 4-8 May 2020. , (10.5194/egusphere-egu2020-11655)
2019
- Yuan, S., Ji, Y., Shi, P., Zeng, J., Gao, J. and Wang, S. 2019. Sparse bayesian learning-based seismic high-resolution time-frequency analysis. {IEEE} Geoscience and Remote Sensing Letters 16(4), pp. 623-627. (10.1109/lgrs.2018.2883496)
- Shi, P., Nowacki, A., Rost, S. and Angus, D. 2019. Automated seismic waveform location using Multichannel Coherency Migration (MCM)—II. Application to induced and volcano-tectonic seismicity. Geophysical Journal International 216(3), pp. 1608-1632. (10.1093/gji/ggy507)
- Shi, P., Angus, D., Rost, S., Nowacki, A. and Yuan, S. 2019. Automated seismic waveform location using multichannel coherency migration (MCM)–I: theory. Geophysical Journal International 216(3), pp. 1842-1866. (10.1093/gji/ggy132)
- Wang, T., Yuan, S., Shi, P., Shuai, D., Luo, C. and Wang, S. 2019. AVAZ inversion for fracture weakness based on three-term Rüger equation. Journal of Applied Geophysics 162, pp. 184-193. (10.1016/j.jappgeo.2018.12.013)
2018
- Shi, P. 2018. Microseismic full waveform modeling and location. PhD Thesis, University of Leeds.
- Shi, P., Yuan, S., Wang, T., Wang, Y. and Liu, T. 2018. Fracture identification in a tight sandstone reservoir: A seismic anisotropy and automatic multisensitive attribute fusion framework. IEEE Geoscience and Remote Sensing Letters 15(10), pp. 1525-1529. (10.1109/LGRS.2018.2853631)
- Shi, P., Angus, D., Nowacki, A., Yuan, S. and Wang, Y. 2018. Microseismic full waveform modeling in anisotropic media with moment tensor implementation. Surveys in Geophysics: An International Review Journal Covering the Entire Field of Earth and Space Sciences 39(4), pp. 567–611. (10.1007/s10712-018-9466-2)
- Yuan, S., Liu, J., Wang, S., Wang, T. and Shi, P. 2018. Seismic waveform classification and first-break picking using convolution neural networks. IEEE Geoscience and Remote Sensing Letters 15(2), pp. 272-276. (10.1109/lgrs.2017.2785834)
2017
- Yan, B., Yuan, S., Wang, S., OuYang, Y., Wang, T. and Shi, P. 2017. Improved eigenvalue-based coherence algorithm with dip scanning. Geophysics 82(2), pp. 1MA-Z12. (10.1190/geo2016-0149.1)
2014
- Chen, Y., Chen, K., Shi, P. and Wang, Y. 2014. Irregular seismic data reconstruction using a percentile-half-thresholding algorithm. Journal of Geophysics and Engineering 11(6), article number: 65001. (10.1088/1742-2132/11/6/065001)
- Chuai, X., Wang, S., Shi, P., Wei, X. and Chen, W. 2014. Applications of texture attribute analysis to seismic interpretation. Journal of Central South University 21(9), pp. 3617–3626. (10.1007/s11771-014-2344-2)
Articles
- He, Y. et al. 2025. Experimental observation of moduli dispersion and attenuation at seismic frequencies in saturated tight rock: effect of microstructure and fluid viscosity. Geophysical Journal International 240, pp. 1308–1330. (10.1093/gji/ggae442)
- Shi, P. et al. 2024. From labquakes to megathrusts: scaling deep learning based pickers over 15 orders of magnitude. Journal of Geophysical Research: Machine Learning and Computation 11(4), article number: e2024JH000220. (10.1029/2024JH000220)
- He, Y. -., Wang, S. X., Tang, G. Y., Dong, C. H., Sun, C., Yuan, S. Y. and Shi, P. D. 2024. Experimental investigation of pore-filling substitution effect on frequency-dependent elastic moduli of Berea sandstone. Geophysical Journal International 238(2), pp. 902–921. (10.1093/gji/ggae195)
- He, Y. et al. 2024. Laboratory experiments and theoretical study of pressure and fluid influences on acoustic response in tight rocks with pore microstructure. Geophysical Prospecting 72(5), pp. 1896-1918. (10.1111/1365-2478.13466)
- Parastatidis, E., Pytharouli, S., Stankovic, L., Stankovic, V., Shi, P. and Hildyard, M. W. 2024. Multichannel coherence migration grid search (MCMgs) in locating microseismic events recorded by a surface array. Geophysical Journal International 236(2), pp. 1042–1052. (10.1093/gji/ggad465)
- Mohammadigheymasi, H. et al. 2023. IPIML: A deep-scan earthquake detection and location workflow Integrating Pair-Input deep learning model and Migration Location method. IEEE Transactions on Geoscience and Remote Sensing 61 (10.1109/tgrs.2023.3293914)
- He, Y. et al. 2023. A physical modelling study of waveform amplification effects of reservoir heterogeneity on time‐lapse seismic attribute analysis. Geophysical Prospecting 71(2), pp. 206-226. (10.1111/1365-2478.13298)
- Yan, B., Ji, Y. and Shi, P. 2023. Frequency-dependent inversion based on spherical-wave reflection coefficient in elastic medium: Theory and methodology. Journal of Applied Geophysics 209, article number: 104908. (10.1016/j.jappgeo.2022.104908)
- Shi, P., Grigoli, F., Lanza, F., Beroza, G. C., Scarabello, L. and Wiemer, S. 2022. MALMI: An automated earthquake detection and location workflow based on machine learning and waveform migration. Seismological Research Letters 93(5), pp. 2467-2483. (10.1785/0220220071)
- Obermann, A. et al. 2022. Combined large-N seismic arrays and DAS fiber optic cables across the Hengill geothermal field, Iceland. Seismological Research Letters 93(5), pp. 2498-2514. (10.1785/0220220073)
- Shi, P., Seydoux, L. and Poli, P. 2021. Unsupervised learning of seismic wavefield features: clustering continuous array seismic data during the 2009 L'Aquila earthquake. Journal of Geophysical Research: Solid Earth 126(1), article number: e2020JB020506. (10.1029/2020JB020506)
- Li, L. et al. 2020. Recent advances and challenges of waveform‐based seismic location methods at multiple scales. Reviews of Geophysics 58(1), article number: e2019RG000667. (10.1029/2019RG000667)
- Yuan, S., Wei, W., Wang, D., Shi, P. and Wang, S. 2020. Goal-oriented inversion-based NMO correction using a Convex l 2,1 -norm. IEEE Geoscience and Remote Sensing Letters 17(1), pp. 162-166. (10.1109/LGRS.2019.2915520)
- Yuan, S., Ji, Y., Shi, P., Zeng, J., Gao, J. and Wang, S. 2019. Sparse bayesian learning-based seismic high-resolution time-frequency analysis. {IEEE} Geoscience and Remote Sensing Letters 16(4), pp. 623-627. (10.1109/lgrs.2018.2883496)
- Shi, P., Nowacki, A., Rost, S. and Angus, D. 2019. Automated seismic waveform location using Multichannel Coherency Migration (MCM)—II. Application to induced and volcano-tectonic seismicity. Geophysical Journal International 216(3), pp. 1608-1632. (10.1093/gji/ggy507)
- Shi, P., Angus, D., Rost, S., Nowacki, A. and Yuan, S. 2019. Automated seismic waveform location using multichannel coherency migration (MCM)–I: theory. Geophysical Journal International 216(3), pp. 1842-1866. (10.1093/gji/ggy132)
- Wang, T., Yuan, S., Shi, P., Shuai, D., Luo, C. and Wang, S. 2019. AVAZ inversion for fracture weakness based on three-term Rüger equation. Journal of Applied Geophysics 162, pp. 184-193. (10.1016/j.jappgeo.2018.12.013)
- Shi, P., Yuan, S., Wang, T., Wang, Y. and Liu, T. 2018. Fracture identification in a tight sandstone reservoir: A seismic anisotropy and automatic multisensitive attribute fusion framework. IEEE Geoscience and Remote Sensing Letters 15(10), pp. 1525-1529. (10.1109/LGRS.2018.2853631)
- Shi, P., Angus, D., Nowacki, A., Yuan, S. and Wang, Y. 2018. Microseismic full waveform modeling in anisotropic media with moment tensor implementation. Surveys in Geophysics: An International Review Journal Covering the Entire Field of Earth and Space Sciences 39(4), pp. 567–611. (10.1007/s10712-018-9466-2)
- Yuan, S., Liu, J., Wang, S., Wang, T. and Shi, P. 2018. Seismic waveform classification and first-break picking using convolution neural networks. IEEE Geoscience and Remote Sensing Letters 15(2), pp. 272-276. (10.1109/lgrs.2017.2785834)
- Yan, B., Yuan, S., Wang, S., OuYang, Y., Wang, T. and Shi, P. 2017. Improved eigenvalue-based coherence algorithm with dip scanning. Geophysics 82(2), pp. 1MA-Z12. (10.1190/geo2016-0149.1)
- Chen, Y., Chen, K., Shi, P. and Wang, Y. 2014. Irregular seismic data reconstruction using a percentile-half-thresholding algorithm. Journal of Geophysics and Engineering 11(6), article number: 65001. (10.1088/1742-2132/11/6/065001)
- Chuai, X., Wang, S., Shi, P., Wei, X. and Chen, W. 2014. Applications of texture attribute analysis to seismic interpretation. Journal of Central South University 21(9), pp. 3617–3626. (10.1007/s11771-014-2344-2)
Conferences
- Finger, C., Tuinstra, K., Niemz, P., Shi, P., Ermert, L. and Lanza, F. 2024. Spatio-temporal evolution of hypocenters and moment tensors derived from time-reverse imaging. Presented at: EGU General Assembly 2024, Vienna, Austria, 14-19 April 2024. , (10.5194/egusphere-egu24-14828)
- Shi, P., Schultz, R., Lanza, F., Scarabello, L., Ermert, L. and Weimer, S. 2024. Machine learning based real-time microseismic monitoring and stimulated fracture characterization at the Utah FORGE Geothermal site. Presented at: EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024. , (10.5194/egusphere-egu24-15621)
- Obermann Anne, A., Goertz-Allmann, B., Sanchez-Pastor, P., Shi, P., Wu, S. and Hjórleifsdóttir, V. 2024. High-resolution seismic methods for geothermal exploration and monitoring across the Hengill volcanic area. Presented at: EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024. , (10.5194/egusphere-egu24-21112)
- Ermert, L., Lanza, F., Ciardo, F., Shi, P., Afanasiev, M. and Wiemer, S. 2023. Modeling the waveforms of induced seismicity sequences with application to Utah FORGE. Presented at: EGU General Assembly 2023, Vienna, Austria, 23 - 28 April 2023. , (10.5194/egusphere-egu23-11883)
- De solda, M., Grigoli, F., Shi, P., Lanza, F. and Wiemer, S. 2023. A deep learning-based workflow for microseismic event detection. Presented at: EGU General Assembly 2023, Vienna, Austria, 23 - 28 April 2023. , (10.5194/egusphere-egu23-1638)
- Shi, P., Lanza, F., Grigoli, F. and Wiemer, S. 2023. Near-real-time microseismic monitoring with machine-learning and waveform back-projection at the Utah FORGE geothermal site. Presented at: EGU General Assembly 2023, Vienna, Austria, 23 - 28 April 2023. , (10.5194/egusphere-egu23-13227)
- Nakata, N. et al. 2023. Elastic Characterization at Utah FORGE: P-wave Tomography and VSP Subsurface Imaging. Presented at: 48th Workshop on Geothermal Reservoir Engineering, California, USA, 6-8 February 2023Proceedings 48th Workshop on Geothermal Reservoir Engineering.
- Mohammadigheymasi, H., Tavakolizadeh, N., Shi, P., Xiao, Z., Mousavi, S. M. and Fernandes, R. 2023. An automated earthquake detection algorithm by combining pair-input deep learning and migration location methods. Presented at: EGU General Assembly 2023, Vienna, Austria, 23 - 28 April 2023. , (10.5194/egusphere-egu23-15180)
- Ermert, L., Lanza, F., Shi, P., Tuinstra, K. and Wiemer, S. 2022. Modeling induced micro-earthquakes for an experimental enhanced geothermal system site. Presented at: 20th Swiss Geoscience Meeting 2022, Lausanne, Switzerland, 18-20 November 2022.
- Shi, P., Grigoli, F., Lanza, F. and Wiemer, S. 2022. MALMI: towards combining machine learning and waveform migration for fully automated earthquake detection and location. Presented at: EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022. Copernicus {GmbH}, (10.5194/egusphere-egu22-6087)
- Parastatidis, E., Pytharouli, S., Stankovic, L., Stankovic, V. and Shi, P. 2021. Minimising the computational time of a waveform based location algorithm. Presented at: EGU General Assembly (online) 2021, Online, 19 - 30 April 2021. , (10.5194/egusphere-egu21-15664)
- Shi, P. 2021. Towards real-time monitoring of induced microseismicity in enhanced geothermal systems. Presented at: 19th Swiss Geoscience Meeting, Geneva, Switzerland, 19-20 November 2021. pp. 19-19.
- Shi, P., Seydoux, L. and Poli, P. 2020. Direct fault states assessment from wavefield properties: application to the 2009 L'Aquila earthquake. Presented at: EGU General Assembly 2020, Online, 4-8 May 2020. , (10.5194/egusphere-egu2020-11655)
Thesis
- Shi, P. 2018. Microseismic full waveform modeling and location. PhD Thesis, University of Leeds.
Research
Induced Seismicity and Geo-energy Applications
Induced seismicity poses significant challenges for geo-energy projects such as enhanced geothermal systems, carbon geological sequestration, and natural gas storage. My research delves into the intricate interplay between fluid dynamics, stress changes, and rock properties to unravel induced seismicity mechanisms under realistic subsurface conditions. By advancing our understanding of these processes, I aim to mitigate induced earthquake risks, enabling safe and sustainable exploitation of geo-energy resources and carbon sequestration practices.
Earthquake Physics and Hazard Mitigation
Understanding earthquake rupture mechanics is a fundamental pursuit in Earth Sciences and is also crucial to mitigating seismic hazards. My research explores earthquake source parameters, including source geometry, focal mechanism, and stress drop to investigate earthquake preparation and nucleation processes. Additionally, I integrate site-specific conditions, fault dynamics, and probabilistic models to improve earthquake risk assessment and forecasting, contributing to proactive hazard mitigation strategies.
Geophysical Monitoring and Imaging for Sustainable Energy
The transition to a sustainable and carbon-neutral future hinges on efficient and safe energy technologies, such as geothermal energy and carbon storage. My research develops innovative geophysical monitoring and imaging methods/tools to maximize energy exploitation and storage efficiency while mitigating potential geo-hazards. The advancements can empower us to identify favorable sites, optimize exploitation strategies, image hidden faults, and effectively de-risk associated processes, supporting the global energy transition.
Earth System Digital Twins and Smart City
Building digital twins of Earth systems and urban environments offers transformative possibilities for hazard forecasting, resilience planning, and urban development optimization. I am particularly interested in integrating geophysical imaging, geospatial data, and simulation techniques, to create multi-scale digital twins. With these innovations, I hope to create highly realistic digital twins that mirror the complexities of the real world across varying scales—from local geological scales and cities to the entire Earth systems, supporting interdisciplinary solutions for smart cities and sustainable development.
Current Project:
- EFFSIMMSI: Advancing Induced Earthquake Forecasting and Fracturing Dynamics via Innovative Scale-Invariant Seismic Monitoring and Multi-Sensor Integration, Swiss National Science Foundation (SNSF) Project Funding, Project PI, Budget: 316’960 CHF.
Teaching
- Hazards, Risk and Resilience
- Environmental and Water Hazards Case Studies
- Petroleum, Geoenergy and Basin Analysis
- Earth and Environmental System Modelling and Applications
- Numerical modelling of Environmental Hazard processes
- Geography Field Skills
Biography
- 2019 Ph.D. in Geophysics, University of Leeds, UK.
- 2015 Master in Applied Geophysics, China University of Petroleum-Beijing, China.
- 2012 Bachelor in Exploration Geophysics, China University of Petroleum-Beijing, China.
Honours and awards
- 2022 Wiley Top Cited Article 2020-2021
- 2021 Outstanding Prize of the 1st BGP Cup Exploration Geophysics Competition
Professional memberships
- American Geophysical Union (AGU)
- European Geosciences Union (EGU)
- European Association of Geoscientists and Engineers (EAGE)
- Society of Exploration Geophysicists (SEG)
Academic positions
- 2024 - Now Lecturer, School of Earth and Environmental Sciences, Cardiff University, UK.
- 2023 - 2024 Senior Researcher (Oberassistent), Swiss Seismological Service, ETH Zürich, Switzerland.
- 2021 - 2023 Postdoctoral Research Fellow, Swiss Seismological Service, ETH Zürich, Switzerland.
- 2019 - 2021 Postdoctoral Research Fellow, ISTerre, Université Grenoble Alpes, France.
- 2015 - 2019 Teaching Assistant, School of Earth and Environment, University of Leeds, UK.
Committees and reviewing
- Reviewer: Nature Communications; Nature Communications Earth & Environment; Geophysical Journal International; Journal of Geophysical Research: Machine Learning and Computation; Seismological Research Letters; Bulletin of the Seismological Society of America; Geophysics; Geophysical Prospecting; Scientific Reports; Frontiers in Earth Science; IEEE Signal Processing Magazine; IEEE Transactions on Geoscience and Remote Sensing; IEEE Geoscience and Remote Sensing Letters; Geomatics, Natural Hazards and Risk; Petroleum Science; Journal of Applied Geophysics; Computers and Geotechnics; Earth, Planets and Space; Energies; Acta Geophysica; Journal of Geophysics and Engineering; Petroleum Science Bulletin; Exploration Geophysics; SN Applied Sciences.
- Organizer and Guest editor of the special issue “Machine Learning Approaches for Geophysical Data Analysis” in Applied Sciences.
Supervisions
- Induced Seismicity and Geo-energy Applications
- AI and Machine Learning Seismology
- Earthquake Physics and Hazard Mitigation
- Earth System Digital Twins and Smart City
- Geophysical Monitoring and Imaging for Sustainable Energy
- Advanced Seismic Monitoring and Real-time Analysis
Past projects
- Advancing Induced Earthquake Forecasting and Fracturing Dynamics via Innovative Scale-Invariant Seismic Monitoring and Multi-Sensor Integration Swiss National Science Foundation (SNSF) Project Funding
Contact Details
Research themes
Specialisms
- Machine learning seismology
- Earthquake physics
- Data science in geophysics
- Geo-energy exploitation
- Geohazard monitoring and mitigation