Machine Learning for Seismology
Deep-learning models for seismic event detection, phase picking, and scientific time-series analysis.
PhD Candidate in Geophysics and Seismology
Mohammad Hossein Khosravi
Ramin · University of Toronto
Geophysicist
I develop machine-learning and high-performance computing workflows for microseismic monitoring, seismic event detection, phase picking, and subsurface characterization.
About
Research Profile
I am a PhD Candidate in Geophysics and Seismology at the University of Toronto. My research focuses on applying machine learning and deep learning to microseismic and earthquake monitoring, particularly for seismic event detection, phase picking, phase association, and hypocenter localization.
My background combines geophysics, petroleum engineering, rock physics, seismic inversion, and scientific computing. I work with large-scale seismic datasets and develop scalable workflows using Python, deep-learning frameworks, seismological software, and high-performance computing systems.
My work aims to improve the accuracy, scalability, and reliability of seismic monitoring workflows for induced seismicity and subsurface characterization applications.
Research
Main Areas
Focused themes across seismology, machine learning, subsurface characterization, and scientific computing.
Microseismic Monitoring and Induced Seismicity
Automated workflows for weak-event detection, phase association, location, catalog construction, and induced-seismicity analysis.
Rock Physics and Seismic Inversion
Rock physics, seismic inversion, AVO analysis, and reservoir characterization.
High-Performance Scientific Computing
Scalable seismic workflows using Python, Linux, SLURM, Singularity, and Compute Canada clusters.
Selected Projects
Current Work
AI-Based Microseismic Monitoring Workflow
An end-to-end workflow for seismic event detection, phase picking, association, and localization using deep-learning models and seismological processing tools.
Deep Learning for Phase Picking
Application and adaptation of deep-learning models for automatic P- and S-wave arrival picking in local microseismic datasets.
Research Outputs
Publications
Journal articles and conference contributions on induced seismicity, microseismic monitoring, deep learning for seismic data, rock physics, and seismic inversion.
Skills
Technical Toolkit
Grouped capabilities for seismic research, data science, and scalable scientific computing.
Programming and Data Science
Machine Learning
Seismology
Geophysics and Rock Physics
HPC and Tools
Contact
Get in Touch
I am open to research collaboration, academic discussion, and opportunities involving machine learning for geophysics and seismic data.
Mohammad Hossein Khosravi
PhD Candidate in Geophysics and Seismology · University of Toronto
mh.khosravi@mail.utoronto.ca
Toronto, Canada