"I like working with scientists to solve problems using digital technologies. Taking an idea and working with a team to develop software and make this a reality really motivates me.
There are people with a range of skills at PML, working to understand and solve some of the environmental challenges we are facing, I enjoy being part of this."
Dan is a Research Software Engineer within the Digital Innovation and Marine Autonomy group at PML where he applies best practices in software engineering to support scientific research, ensuring computational resources are used as efficiently as possible. He primary works with geospatial data using a range of techniques, including Machine Learning and Artificial Intelligence. Dan participates in a range of research projects and service delivery.
Dan studied at Aberystwyth University, starting with an undergraduate degree was in Physics, followed by a MSc in Geographical Information Systems and Remote Sensing then a PhD investigating the retrieval forest structure from Synthetic Aperture Radar data in the Department of Geography. After graduating from his PhD, Dan spent two years as a postdoctoral research fellow in the Microwave Systems Sensors and Imaging Lab (MiXIL) at the University of Southern California.
Dan joined PML in 2014 to work as part of the NERC Airborne Research and Survey Facility Data Analysis Node and in 2019 became manager of the NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS). Dan is interested in all aspects of Digital Research Infrastructure and chairs the High Performance Computing Strategy Group at PML.
- NEODAAS (2019 - Present)
- BICOME (2022 – 2024)
- BOOMS (2022 – 2024)
- Vis4Sea (2023 – 2025)
- Living Wales Phase III (PML Applications; 2023 – 2024)
- Living Wales Phase II (2021 - 2023)
- Digital Earth Australia Land Cover Mapping (2018 – 2020)
- NERC-ARF-DAN (2014 – 2019)
Recent publications
- Wilkes, P; Disney, M; Armston, J; Bartholomeus, H; Bentley, L; Brede, B; Burt, A; Calders, K; Chavana‐Bryant, C; Clewley, D; Duncanson, L; Forbes, B; Krisanski, S; Malhi, Y; Moffat, D; Origo, N; Shenkin, A; Yang, W; 2023. TLS2trees: A scalable tree segmentation pipeline for TLS data. Methods in Ecology and Evolution.
- Cayetano, CB; Creencia, LA; Sullivan, E; Clewley, D; Miller, PI; 2023. Multi-spatiotemporal analysis of changes in mangrove forests in Palawan, Philippines: predicting future trends using a support vector machine algorithm and the Markov chain model. UCL Open Environment.
- Martin, N; Clewley, D; Groom, SB; 2023. Improving the performance of National Centre for Earth Observation (NCEO) code using GPUs. .
- Owers, CJ; Lucas, RM; Clewley, D; Tissott, B; Chua, SMT; Hunt, G; Mueller, N; Planque, C; Punalekar, SM; Bunting, P; Tans, P; Metternicht, G; 2022. Operational continental-scale land cover mapping of Australia using the Open Data Cube. International Journal of Digital Earth.
- Watson-Parris, D; Christensen, MW; Laurenson, A; Clewley, D; Gryspeerdt, E; Stier, P; 2022. Shipping regulations lead to large reduction in cloud perturbations. Proceedings of the National Academy of Sciences.