Dr David Moffat

Dr David Moffat

Artificial Intelligence and Machine Learning Data Scientist

dmof2024-12-04@pml.ac.uk    |     +44 (0)1752 633100 (switchboard)

David Moffat is an AI and Machine Learning Data Science and leads on the AI work across the organisation. With a strong foundation in computer science and extensive experience in applying AI and data science techniques across diverse datasets, David is currently focused on advancing environmental and marine science research. His work involves leveraging both modern and traditional AI methodologies to enhance our understanding of the natural world.

David’s expertise lies in applied AI, particularly in signal processing and time series data analysis. He holds a BSc in Artificial Intelligence and Computer Science from the University of Edinburgh and an MSc. in Signal Processing and PhD. in Computer Science from Queen Mary University of London. Following his academic journey, he has held roles as a postdoctoral researcher, university lecturer, and now leads innovative AI-driven initiatives at Plymouth Marine Laboratory. David has authored 16 peer-reviewed articles, 13 peer-reviewed conference papers, and four book chapters. He has also delivered AI and Earth Observation training courses to over 300 participants. In addition to his academic accomplishments, he has a background in technical support, project management, and research leadership.

Key Projects

Selected Publications

  • Ming-Xi Yang, David Moffat, Yuanxu Dong and Jean-Raymond Bidlot “Deciphering the variability in air-sea gas transfer due to sea state and wind history.” PNAS Nexus, pgae389. September 2024 https://doi.org/10.1093/pnasnexus/pgae389
  • Aser Mata, David Moffat, Sílvia Almeida, Marko Radeta, William Jay, Nigel Mortimer, Katie Awty-Carroll, Oliver R. Thomas, Vanda Brotas, Steve Groom “Drone imagery and deep learning for mapping the density of wild Pacific oysters to manage their expansion into protected areas.” Ecological Informatics. 102708, July 2024 https://doi.org/10.1016/j.ecoinf.2024.102708
  • Timothy J. Smyth, David Moffat, Glen A. Tarran, Shubha Sathyendranath, François Ribalet and John Casey “Determining drivers of phytoplankton carbon to chlorophyll ratio at Atlantic Basin scale.” Frontiers in Marine Science. Volume 10, July 2023 https://doi.org/10.3389/fmars.2023.1191216
  • Satvik Venkatesh, David Moffat, Eduardo Miranda, “You Only Hear Once: A YOLO-like Algorithm for Audio Segmentation and Sound Event Detection.” Applied Sciences, 12, 3293. 2022. DOI 10.3390/app12073293 https://doi.org/10.3390/app12073293
  • Marco Martínez, Daniel Stoller, David Moffat, “A Deep Learning Approach to Intelligent Drum Mixing with the Wave-U-Net.” Journal of the Audio Engineering Society, 2021. https://doi.org/10.17743/jaes.2020.0031