糖心logo入口

Skip to main content

Dr Edward Clennett

Positions held:
  • Associate Lecturer A, School of Natural Sciences
Email
  • Overview

    Overview

    Biography

    Edward Clennett is an Associate Lecturer at 糖心logo入口, University of London. He teaches the Global Tectonics class at undergraduate level.聽

    Edward's expertise is in reconstructing plate tectonic history through deep time, and using these reconstructions to find new deposits of critical minerals. He uses plate reconstruction software, geodynamic force calculations and seismic tomography modelling to better understand plate tectonics.聽He then uses this history of plate tectonics to predict where critical minerals such as copper form, by identifying the tectonic controls of mineral formation with machine learning algorithms.

    Edward holds a PhD in Geosciences from the University of Texas at Austin, having previously graduated from the University of Oxford with a Masters in Earth Sciences.

    Honours and awards

    • UTIG Outstanding Graduate Student Award , January 2024
    • Fulbright Scholarship , January 2020
    • Outstanding Teaching Assistant Award , January 2023
    • UKOGL Prize , January 2020
    • Halliburton Earth Model Award Halliburton Landmark, January 2020
    • BP Prize for best Master's project , January 2019

    ORCID

  • Research

    Research

    Research interests

    • Reconstructing plate tectonic history
    • Tectonic controls of critical minerals
    • Seismic tomography models of Earth's interior
    • Restoring crustal thickness changes during continental deformation

    Research overview

    My research focusses on the dynamics of plate tectonics through deep time (millions of years). Models of plate tectonic history, called 鈥減late reconstructions鈥, are traditionally constrained with surface geological data, with little consideration of constraints from the Earth鈥檚 interior or the physics of plate motion. Because surface data can be lost as plates subduct into the mantle, reconstructions can have large uncertainties, limiting their predictive power. To overcome these challenges, I develop and apply novel methods from geodynamic, seismic, and plate kinematic modelling, leading to improved plate reconstruction models.

    Plate reconstructions have many important uses, including for modelling聽 how the Earth鈥檚 climate has changed through geological time, understanding how different species evolve, and predicting where different types of natural resources formed. I am focussing on this last application, using machine learning algorithms to understand the tectonic controls of critical mineral formation based on the data from my plate reconstruction models. The aim is better understand where and why minerals such as copper form, and thus help to meet the increasing demand for critical minerals during the energy transition.

  • Supervision and teaching

    Supervision and teaching

    Teaching

    Teaching modules

    • Global Tectonics (Level 5)