Opportunities

  • I will be supervising a project on Deep Learning Optimization and Design Choices for Marine Biodiversity Monitoring with Dr. De Clippele (University of Glasgow) within the Leverhulme Programme for Doctoral Training in Ecological Data Science. Applications due: 7 March 2025. All info on: https://ecological-data-science.github.io
    Please don’t hesitate to reach out to me if you are interested in applying for this opportunity.

  • Further, I am a PhD supervisor within the DiveIn CDT. This CDT prioritises diversity and aims to produce transformative interdisciplinary research in various areas, including Net Zero and AI. More information: DiveIn CDT and my supervisor profile
    If you have been accepted onto the CDT, please do not hesitate to reach out to me if you are interested in my work.

Upcoming Supervision

  • The marine rewilding effect: Building a cost-effective framework for measuring Marine Net Gain project with Dr. De Clippele (main, University of Glasgow), Dr. Hogdson (CreditNature), and Dr. Wartmann (University of Aberdeen) within the NETGAIN CDT.
  • Developing GPU-accelerated digital twins of ecological systems for population monitoring and scenario analyses project with Prof. Torney (main, University of Glasgow), Prof. Morales (University of Glasgow), Prof. McCrea (Lancaster University), and Prof. Husmeier (University of Glasgow) within the ExaGEO CDT.
  • UG Summer Research project on Monitoring vegetation patterns from drone imagery using machine learning, with Dr. Eizenhöfer (University of Glasgow).

Current and Previous Supervision:

  • AIMS Ghana MSc in Mathematical Sciences projects.
  • EPSRC Vacation Internship on physics-informed neural networks.
  • Level 4 Projects on neural network optimisation.
  • MSci project with industry co-supervisor Dr. Hodgson (CreditNature) on Simulating Scottish Ecosystems for Landscape Ecology Metrics.
  • Deploying deep learning for marine biodiversity monitoring with Dr. De Clippele (main, University of Glasgow) and Dr. Smith (University of Copenhagen) within the Leverhulme Programme for Doctoral Training in Ecological Data Science.