School of Earth and Environment

Matthew Gaddes Matthew Gaddes

Postgraduate Researcher

Email address:
Room: 8.153

Affiliation: Institute of Geophysics and Tectonics


I am a PhD student working with Prof. Andy Hooper to detect signs of volcanic unrest in InSAR time series acquired by the Sentinel-1 satellites. We aim to achieve this through the application of several machine learning methods, and consequently during the course of my Phd I have become familiar with:

  • Blind signal separation methods:
    • Principal component analysis (PCA).
    • Spatial and temporal independent component analysis (ICA).
    • The ICASO algorithm for assessing the reliability of ICA results.
    • Non-negative matrix factorisation (NMF).

  • Manifold learning methods:
    • Multidimensional scaling (MDS).
    • t-distributed stochastic neighbour embedding (t-SNE).

  • Clustering methods:
    • Agglomerative clustering.
    • Density-based spatial clustering of applications with noise (DBSCAN).
    • Hierarchical DBSCAN (HDBSCAN).

  • Neural networks:
    • Use of Keras with Tensorflow.
    • Training of convolutional neural networks (CNN).


  • PhD Candidate in Tectonics, 2014 - present
  • M Earth Sci., The University of Oxford, 2006-2010

Research Interests

Automatic detection of volcanic unrest from space

Teaching Interests

Computational inverse theory.



I am funded by the "Looking inside the continents from space" (LiCS) project.