David Zivuku

Data Science: Experienced in data collection, preprocessing, and analysis, applying statistical and machine learning techniques to extract insights and support decision-making.

GIS (Geographic Information Systems): Skilled in spatial data management, mapping, and geospatial analysis using tools such as ArcGIS and QGIS to visualize and interpret geographic patterns.

Sound Analysis: Proficient in acoustic signal processing, including spectral analysis, filtering, and interpretation of audio data for research and applied projects.

Frequency Analysis: Strong background in Fourier transforms, spectral decomposition, and frequency-domain modeling to identify key signal characteristics.

Vibration Analysis: Experienced in monitoring and analyzing vibration data for structural health, mechanical systems, and environmental studies, applying both time-domain and frequency-domain techniques.

Interdisciplinary Integration: Adept at combining geospatial insights with signal and vibration data to support complex projects in engineering, environmental monitoring, and AI-driven applications.

BSc (Hons) Geography and Environmental Science, specialising in GIS

BSc (Hons) Music and Musicology, specialising in Sound, Frequency and Vibration