https://www.simmonslab.com/about daily 0.75 2021-12-29 https://www.simmonslab.com/people daily 0.75 2025-05-20 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1641837153369-G4FMN575UQYGLGV6QOLB/photoOfMe.jpg People https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1641837173249-193RGNGWD6RUBXUZT7KF/55ACDF5D-82D0-4AFC-8388-DCD6861F9A74.jpeg People https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1641837235724-2CBWYWG4PHL1S4JLEZ40/Trish_Nowak.jpeg People https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1650928459994-5YOAFGHBJJ53042BCTI3/72F5EA83-7A48-4379-90C3-EC6F9552D7B5.jpeg People https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/f9ec6952-edb5-4d43-9dbb-9ed1247533fd/thumbnail_CDT+Headshot+Upper+Torso+4to3.jpg People https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/4021fb3f-3585-4df9-9fbb-67f675c0d497/WR-PIC.jpg People https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/c00775c6-a941-4c65-8d43-e96b85500ae0/p1000137-c1.jpg People https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/c7ac0577-e83c-4235-995a-8e7efba4474c/VD-Photo.png People https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/3cb2fc2c-f465-43ae-808c-900228bf91cb/Thomas+O%27Shea-Wheller.jpg People https://www.simmonslab.com/contact daily 0.75 2022-01-29 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/2cbb83c1-751b-4472-9f91-ab63c337c286/email_and_twitter.png Contact - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://www.simmonslab.com/join-the-lab daily 0.75 2024-07-04 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1642703396769-CPG0TLDM712HVRKJBLVX/unsplash-image-PvBECXDZw84.jpg Join the lab We’re always interested in growing our group, so if you’re interested in joining then get in touch. We’re flexible and support remote working. Below are some possible funding opportunities and courses: Masters A range of MRes and MSc programmes at Exeter Biosciences MSc Applied Data Science (Ecology and Evolution) PhD NERC GW4+ DTP Environmental Intelligence CDT BBSRC South West Biosciences Doctoral Training Partnership EPSRC DTP Postdoc 1851 Research Fellowships Newton International Fellowships Marie Skłodowska-Curie Actions Individual Fellowships Leverhulme Early Career Fellowships Other fellowships https://www.simmonslab.com/benno-simmons daily 0.75 2023-09-22 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/f5b1993d-8242-41fa-afdb-67082756c339/96C06841-27FF-48BA-A09D-B23B6A2CDC1D.jpeg Benno Simmons - Benno Simmons I’m a Lecturer in Ecological Data Science at the University of Exeter, where I lead the Simmons Lab. I did my undergraduate at the University of Oxford, Masters at Imperial College London, and PhD at the University of Cambridge, under the supervision of William Sutherland and Lynn Dicks. I then did a postdoc at the University of Sheffield, before joining Exeter in 2019. I’m interested in using data science and technology to understand and reverse biodiversity loss. I have broad interests within this theme, and so work in the group spans a wide range of topics and methods. https://www.simmonslab.com/jake-curry daily 0.75 2023-03-21 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1641837153369-G4FMN575UQYGLGV6QOLB/photoOfMe.jpg Jake Curry - Jake Curry I am interested in the use of cutting-edge computing tools to aid research in the fields of ecology and conservation. My PhD is focused on using deep learning approaches to automate the analysis of large camera trap data sets (such as identifying species in images). If the analysis of camera trap data can be fully automated, this paves the way for camera traps to be used as a low-cost, automatic and scalable tool for global biodiversity monitoring. https://www.simmonslab.com/jonathan-growcott daily 0.75 2023-03-21 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1641837173249-193RGNGWD6RUBXUZT7KF/55ACDF5D-82D0-4AFC-8388-DCD6861F9A74.jpeg Jonathan Growcott - Jonathan Growcott My interests lie in the utilisation of technology for ecological and conservation practices. Previously, I completed my MBiol (Hons) in Biosciences at Durham University where I analysed acoustic data collected from autonomous recording units. For my PhD, I am now combining multiple remote data capture technologies (specifically camera traps and bioacoustic microphones) to automatically monitor species populations in African savannah ecosystems, with a particular focus on lions. This will involve both extensive fieldwork in Africa and desk-based computational work to develop AI models. Email: jlg230 [AT] exeter [DOT] ac [DOT] uk Twitter: @J_Growcott99 https://www.simmonslab.com/trish-nowak daily 0.75 2022-10-01 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1641837235724-2CBWYWG4PHL1S4JLEZ40/Trish_Nowak.jpeg Trish Nowak - Trish Nowak I am a PhD student with a background in Physical Geography (BSc hons 1st) and Oceanography (MSc, Phys & Bio). My current project focuses on utilising machine learning methods to gain better understanding of environmental processes. This method offers possible clues on causality of processes, rather than just correlation between parameters. In particular my research will focus on a journey of Saharan mineral dust and its further impact on: displacement of West African Monsoon system, biogeochemical cycles and productivity of central Atlantic Ocean, and biogeochemical cycles and the productivity of the Amazon rainforest. For example, the Amazon rainforest's soils are found to be nutrient poor, with no clear sources of essential micro- and macronutrients (phosphorous and iron in particular). Current theory of Saharan mineral dust enriching Amazon rainforest soils is fairly well known. However, annual quantity estimates of transported dust (and thus the nutrients) yield large uncertainties and vary between the studies. The power of machine learning may provide us with reduced uncertainties, better estimates and perhaps suggest missing links. ML's ability to analyse dozens of parameters over decades of data sets may unveil new or previously overlooked causalities. The possibility of solving a long standing scientific question is what inspires me to do my research. https://www.simmonslab.com/publications daily 0.75 2025-12-02 https://www.simmonslab.com/research daily 0.75 2023-08-06 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1643076492967-UG35QUXMLTULJ5LIGSLY/unsplash-image-QfefrzHQAdM.jpg Research - Global biodiversity change and conservation Work in the global biodiversity change and conservation theme uses large datasets to answer applied questions at large - often global - scales. Currently, we have three main projects within this theme: (i) trying to understand, and predict, the impacts of invasive species on ecological communities, (ii) using tools from mathematics to transform our ability to monitor the health of communities, and (iii) using large datasets of population trends to understand the patterns and processes of global biodiversity change. We are also involved in side projects to assess how well evidence of the effectiveness of conservation interventions is conserved across space, and to explore how planetary boundaries interact to affect sustainable food production. Other past side projects in this theme include trying to understand the impacts of protected areas on species populations worldwide; assessing the global impacts of land-use change on biodiversity; exploring the evidence for worldwide insect declines; and assessing the costs and benefits of high-yield farming. https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1643076462239-RMADD71GUOQE4FLEZUHW/unsplash-image-PdPKIkd1L9g.jpg Research - Applied remote sensing Work in this theme uses remote sensing systems – such as satellites or LIDAR sensors – to deliver applied insights. Currently, our main project in this area is using novel machine learning methods and satellite data to forecast the productivity of the Amazon rainforest. Other areas of interest include forecasting deforestation and spatial prioritisation of nature-based climate change solutions. https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1643076558654-YJZF1CIWWZCNVS3D82LO/unsplash-image-CBQd3J4C4DI.jpg Research - Technology for conservation Technology has enabled a wide range of automated and relatively inexpensive sensors to be deployed. These include camera traps, microphones for bioacoustics, environmental data loggers, phenology cameras and GPS tags. We’re interested in using these sensors to solve conservation problems. Current work in this theme includes using deep learning to automate the detection of rare species in camera trap images, and combining camera traps and bioacoustics to automatically monitor lion populations in Africa. https://www.simmonslab.com/home daily 1.0 2024-07-04 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/1643077861282-5K6YF7TZ35RR6BLI0NZQ/unsplash-image-VV2_XVEjg5w.jpg Home https://www.simmonslab.com/ben-fitkovnorris daily 0.75 2023-03-21 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/f9ec6952-edb5-4d43-9dbb-9ed1247533fd/thumbnail_CDT+Headshot+Upper+Torso+4to3.jpg Ben Fitkov-Norris - Ben Fitkov-Norris My PhD work is focused on the role other effective area-based conservation measures can play, alongside protected areas, in conserving marine biodiversity. I’m interested in the biodiversity benefits that can arise from anthropogenic features, such as wind farms, shipwrecks or aquaculture, and how these interface with the existing network of marine protected areas. Departmental page Twitter https://www.simmonslab.com/will-rees daily 0.75 2024-04-04 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/4021fb3f-3585-4df9-9fbb-67f675c0d497/WR-PIC.jpg Will Rees - Will Rees I am a PhD student with a background in Geography (BA Hons), Climate Change (MSc), and over 7 years of industry experience as an Ecological Consultant. My research interests centre around leveraging technology to facilitate landscape-scale decision-making and enhance biodiversity monitoring. My research delves into the relationship between biodiversity and solar farms, aiming to optimise their siting and design to mitigate adverse impacts on landscape connectivity while maximising habitat benefits within solar landscapes. The research will employ AI techniques to enable landscape-scale and long-term ecological monitoring using both acoustic and video data. https://www.simmonslab.com/ross-gardiner daily 0.75 2024-04-04 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/c00775c6-a941-4c65-8d43-e96b85500ae0/p1000137-c1.jpg Ross Gardiner - Ross Gardiner I am a PhD student within the UKRI Environmental Intelligence CDT. My background is as a technologist - I have an MEng degree (1st class) in Electronic and Software Engineering (University of Glasgow) and I have 4+ yrs experience working in various roles comprising AI research, software design, and electronic circuit engineering/manufacture. I am interested in how technology can be used to retreive biodiversity information from the natural environment. In particular, I wish to develop scalable and trustworthy methodologies for monitoring insect biodiversity in a world where the rapid decline of insects is poorly understood/observed. Emerging technologies will play a key role; I am focussed on AI algorithm development, computer vision techniques and digital signal processing. Github: https://github.com/rossGardiner Twitter (X): https://twitter.com/Ross__Gardiner LinkedIn: https://www.linkedin.com/in/ross-g/ University Profile: https://mathematics.exeter.ac.uk/people/profile/index.php?web_id=rg654 https://www.simmonslab.com/viktor-domazetoski daily 0.75 2025-01-08 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/c7ac0577-e83c-4235-995a-8e7efba4474c/VD-Photo.png Viktor Domazetoski - Viktor Domazetoski I am a PhD student within the Biological Sciences (QUEX) programme, a joint degree in collaboration with the University of Queensland, focusing on responsible AI for biodiversity monitoring. I have an interdisciplinary background both in Ecosystem Analysis and Modelling (University of Göttingen), and Data Science (Ss. Cyril and Methodius University of Skopje). Throughout the past years I have worked on the application of statistical methodologies and AI across environmental fields such as plant macroecology, functional ecology and coral reef monitoring, as well as physics, biomedicine and neuroscience. My research centres around the role of responsible AI in biodiversity monitoring. AI holds great promise, but also can cause harms if not developed responsibly. Camera trap AI is nascent and often highly inaccurate, yet is being deployed widely today. This is concerning given that we currently have no understanding of how accurate these systems need to be, or the consequences if they are not. Bad AI systems could miss species declines, resulting in bad conservation outcomes and misallocation of funds. My PhD will develop the first research into responsible AI for biodiversity monitoring, allowing the full potential of this technology to be harnessed. https://www.simmonslab.com/thomas-oshea-wheller daily 0.75 2025-05-20 https://images.squarespace-cdn.com/content/v1/61cc9fc7cd35e318b67275fa/3cb2fc2c-f465-43ae-808c-900228bf91cb/Thomas+O%27Shea-Wheller.jpg Thomas O'Shea-Wheller - Thomas O'Shea-Wheller I am interested in the complex interactions that govern collective behaviour, ecology, and self-organisation within social insects. As a Research Fellow based at the University of Exeter, I leverage deep learning to explore network dynamics, social plasticity, and behavioural heterogeneity in colonies of ants, bees, hornets, and termites. A uniting theme of this work is the study of emergent collective processes to address applied challenges in ecology, specifically via enhanced understanding of their mechanistic bases. As such, my current projects centre upon collective decision-making in ants and termites, social immunity in bees, the role of eusociality in invasive success, and the development of AI-based detection and tracking systems.