Forskerinteresser My research centres on advancing our understanding of earthquake and general seismic processes through the development and application of innovative observational, analytical, and modelling techniques. I work at the intersection of seismology, signal processing, and environmental geophysics, with a particular focus on high-resolution seismic monitoring of natural and anthropogenic sources across diverse settings. My work encompasses microseismicity and induced seismicity, improving event detection, location, and characterization, including studies of seismicity in offshore environments such as the North Sea and controlled energy-related activities like geothermal and CO₂ storage projects. A core theme in my research is the integration of novel sensing technologies, including distributed acoustic sensing (DAS) on fibre-optic networks, which enables real-time and large-scale surveillance of seismic and acoustic events. This has applications ranging from submarine seismic monitoring to urban and infrastructure environments. I lead interdisciplinary projects that leverage machine learning and advanced signal processing to extract meaningful information from complex datasets, such as automatic identification of seismic phases, urban seismic noise classification, and rapid hazard assessment. This work supports practical societal needs, including seismic hazard analysis, urban risk management, and the development of robust seismic monitoring frameworks for emerging energy technologies.

Forskerinteresser Ben Dando is Head of Department at NORSAR, responsible for seismology and verification activities as part of Norway’s National Data Centre for the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Working on behalf of the Norwegian Ministry of Foreign Affairs, he contributes to international treaty verification and seismic data analysis. His work focuses on developing and applying advanced methods for seismic monitoring, waveform analysis, and the detection of natural and anthropogenic seismicity. His research interests include seismic location methods, array and signal processing, forensic seismology, and the use of emerging technologies such as Distributed Acoustic Sensing (DAS) and machine learning for enhanced event detection and characterisation. Ben holds a PhD in earthquake seismology from the University of Leeds and a Master’s degree from University College London.