Tom's research focuses on the application of new methods and technologies to biodiversity monitoring.
His interests span the fields of ecology, computer science, engineering, and citizen science. Tom started his career as a field ecologist studying the behavioural ecology of bats however over the subsequent decades he has increasingly focused on how new technologies can improve the quality and quantity of biodiversity information we have available, as well as increasing access to these data. Tom has used high performance computing, drones, smartphone applications, and AI to support his research into biodiversity monitoring. This work includes projects focused on supporting citizen scientists to monitor the environment, creating tools to support stakeholders access to biodiversity information, developing large scale computing workflows to support long term national scale analysis, and the development of hardware systems to monitor insects, including computer vision tools for interpreting outputs.
Tom places a high value on knowledge exchange activities and as such is involved in a number of national and international networks with ambitions too share and better our understanding how technology can support our understanding of the natural world. Tom currently chairs the COST Action network InsectAI which aims to grow and share knowledge in Europe on methods for imaging and identifying insects using novel sensors and AI techniques.
Terry J. Christopher D. et al. , (2020), Thinking like a naturalist: enhancing computer vision of citizen science images by harnessing contextual data. Methods in Ecology and Evolution, 11, 303-315, http://dx.doi.org/10.1111/2041-210X.13335
August Tom et al. , (2020), Data-derived metrics describing the behaviour of field-based citizen scientists provide insights for project design and modelling bias. Scientific Reports, 10, http://dx.doi.org/10.1038/s41598-020-67658-3