AI-powered earthquake catalog
Developing methods that can assist earthquake detection, phase picking, event association, catalog enrichment, and generation of timely, reviewable earthquake records from continuous seismic data.
TRACE
Türkiye Real-time AI Catalog for Earthquake Monitoring and Early Warning brings together seismology, machine learning, and real-time data systems.
Project scope
TRACE focuses on the main research components needed for AI-assisted earthquake analysis, monitoring, and early-warning research in Türkiye. The project scope connects real-time catalog generation, monitoring workflows, validation, and reusable scientific outputs.
Real-time monitoring workflows
Studying low-latency workflows that connect seismic data streams, model outputs, quality indicators, uncertainty information, and expert review for monitoring-oriented research.
Early-warning research
Exploring analysis methods, latency constraints, reliability requirements, and uncertainty reporting that may contribute to scientifically validated early-warning research pipelines.
Research topics
Seismology
Connecting earthquake science, observation networks, and expert interpretation to support reliable monitoring and catalog research.
Signal Processing
Analyzing continuous seismic time series through filtering, feature extraction, phase information, and noise-aware waveform methods.
Artificial Intelligence
Studying machine learning methods for detection, picking, signal characterization, uncertainty estimation, and catalog enrichment.
Applied Mathematics
Developing models, optimization strategies, statistical evaluation, and uncertainty-aware methods for real-time seismic analysis.
Computational Applications
Building reproducible pipelines, scalable data processing, and software workflows for operational earthquake-monitoring research.
Data Analysis & Visualization Tools
Designing tools that help researchers inspect signals, compare model outputs, evaluate catalogs, and communicate results.
Team
TRACE will be conducted by a core project team in collaboration with researchers, students, engineers, and partner contributors.
Team member 4
Data systems engineer
TRACE project team
Team member 5
Software engineer
TRACE project team
Institutions and support
TRACE is conducted at Boğaziçi University Kandilli Observatory and Earthquake Research Institute with support from Google.org.
Boğaziçi University
Kandilli Observatory and Earthquake Research Institute
Supported by Google.org
Contact
For questions about TRACE, collaboration opportunities, student involvement, or future project outputs, please contact the project team.