Geophysicist & Seismologist
📍 Zürich, Switzerland
Specialised in seismology, signal processing, and machine learning for real-time monitoring systems. Experienced in developing operational seismic workflows, applying advanced quantitative methods to time-series data, and translating research methods into robust scientific software for monitoring applications.
I am a geophysicist specialised in seismology, signal processing, and machine learning for real-time monitoring systems. Experienced in developing operational seismic workflows, applying advanced quantitative methods to time-series data, and translating research methods into robust scientific software for monitoring applications.
Throughout my career, I have developed operational seismic workflows at the intersection of seismology, data science, and engineering—from real-time earthquake early warning systems to structural health monitoring. My work focuses on applying rigorous quantitative methods to time-series data and building reproducible, scalable scientific software.
With a strong foundation in Python scientific computing, machine learning frameworks (PyTorch, TensorFlow), and seismological tools (ObsPy), I have contributed to projects spanning earthquake early warning in Nepal, synthetic waveform generation using generative deep learning, and automated processing pipelines for structural monitoring.
Swiss Seismological Service
IRMOS AG
Swiss Seismological Service
Geophysical Institute [CAS]
Grillo/OpenEEW System
ETH Zürich
2023 – 2025
Specialized in seismology, machine learning applications to geophysical data, and earthquake early warning systems. Master's thesis focused on using generative deep learning models to optimize EEW algorithms through synthetic waveform generation.
Charles University in Prague
2019 – 2022
Awarded Best Bachelor Thesis by the EAGE local chapter Prague for research on real-time magnitude estimation using MEMS-based accelerometers. Received Merit Scholarship from Faculty of Sciences for academic excellence.
Proficient in Python ecosystem for scientific computing and data analysis, with extensive experience in seismological libraries and deep learning frameworks for research and operational applications.
Specialized in analyzing complex geophysical datasets, including seismic waveforms and structural vibration data, using advanced statistical and numerical methods to extract meaningful insights.
Experienced in applying machine learning techniques to geophysical problems, with particular expertise in generative models for synthetic data creation and deep learning for seismic event detection and characterization.
Practical experience in developing and deploying operational monitoring systems for seismic hazard assessment and structural health evaluation, combining theoretical knowledge with real-world engineering constraints.
Proficient in modern scientific software engineering practices including version control, containerisation, and high-performance computing environments to build reproducible and scalable research workflows.
Skilled in creating compelling data visualizations and managing geospatial data for scientific communication, reporting, and decision support.
Multilingual professional capable of collaborating in international research environments and communicating with diverse stakeholders.
BGC Engineering Canada | Jun. 2026 – Aug. 2026
Selected participant in an international research program focused on applied geoscience and natural hazard modelling.
GeoInquire Italy | 2026
Worked on integrated hazard modelling approaches, combining seismic and tsunami processes in a collaborative research environment.
UCL Warning Research Centre | 2023
Participation in interdisciplinary conference focused on inclusive early warning system design and implementation.
Prague, Czechia | 2025 - ongoing
Organizing and coordinating scientific outreach initiatives and career networking events that bridge the gap between students, academic institutions, and private sector partners. These events facilitate knowledge exchange, promote career opportunities in geosciences, and strengthen collaboration between university departments and industry stakeholders.
Sicily, Italy | 2022
Developed innovative virtual field excursions using drone-based data acquisition and 3D modeling techniques. This interdisciplinary bottom-up project combined geoscience fieldwork, remote sensing technology, and educational methodology to create immersive online learning experiences, making geological field sites accessible to students regardless of physical location or mobility constraints.
Faculty of Sciences, Charles University in Prague | 2021 - 2022
Honorary award by the EAGE local chapter Prague | 2022
European Geosciences Union (EGU), Vienna, Austria – 2026
Poster presentation. doi:10.5194/egusphere-egu26-20840
In Submission: Colosimo, F. A., Jozińović, D., and Böse, M.
Institute for Rock Magnetism (IRM) – 2021
Kletetschka et al., 2021.
Check out my code repositories, research projects, and open-source contributions.
Visit GitHub →Connect with me professionally and view my career journey and accomplishments.
Visit LinkedIn →Interactive platform for earthquake early warning and seismic monitoring solutions.
Visit Sweet Seismic →Developing a ground-motion-envelope-based goodness-of-fit algorithm using machine learning generated templates.
Optimising EEW algorithms with synthetic waveforms from generative deep learning models.
View Publication →Using MEMS-based accelerometers and data from the Mexican Grillo network for magnitude estimation.
View Thesis →Organizing scientific outreach and student career networking events, coordinating collaboration between university departments and private sector partners.
An innovative bottom-up project to design online virtual excursions, including drone surveys.
I'm always open to discussing new opportunities, collaborations, or just connecting with fellow professionals in geophysics and seismology.