PhD Student
Coral Reefs
Marine biology
Contact details

Institute of Zoology
Zoological Society of London
Regent's Park

Google Scholar

Ben's research focuses on ways we can support tropical reef conservation and restoration with artificial intelligence. 

Ben is a PhD student at ZSL and UCL, supported by the Fisheries Society of the British Isles. During his PhD, Ben has been working to develop machine-learning techniques to monitor and support coral reef conservation. This is in close cooperation with his industry partner Mars, who operate the world’s largest coral reef restoration program using the MARRS technique (, and a collaborative group of restoration scientists.

Ben's work to date has primarily focused on monitoring coral reefs using their ‘soundscape’. This has included the development of low-cost recording technology and machine learning driven analysis. A significant portion of this has focused on tracking recovery on restored reefs, research which won the prestigious 2023 NetExplo award for the top digital innovation for sustainability globally. Ben continues to advance this work using datasets from around the world.

Hope and Island

Additional applications of machine learning for reef conservation Ben is working on include the detection of illegal bomb fishing. At reefs where Mars have implemented restoration in Indonesia, bomb fishing has been the primary cause of their initial destruction. Ben is also leading on a project which uses computer vision to track the progress of reef restoration from image data and other related work.

Ben strongly believes communicating conservation challenges and successes is key to progress in this area. If you’re interested to read more, take a lot at Ben's previous media interviews or blog posts below.

Professional history

2023-2023 (6 months): Science Officer at Mars Inc 
2022-present: Reef Conservation UK Committee Member 
2021-present: PhD student at UCL and ZSL
2020-2021: Research Associate, University 
2019-2021: MbyRes in Biological Sciences from the University of Exeter
2015-2019: BSc (Hons) in Biological Sciences from the University of Exeter


Williams, B., Lamont, T.A., Chapuis, L., Harding, H.R., May, E.B., Prasetya, M.E., Seraphim, M.J., Jompa, J., Smith, D.J., Janetski, N. and Radford, A.N., 2022. Enhancing automated analysis of marine soundscapes using ecoacoustic indices and machine learning. Ecological Indicators, 140: 108986. doi:

Lamont, T.A., Chapuis, L., Williams, B., Dines, S., Gridley, T., Frainer, G., Fearey, J., Maulana, P.B., Prasetya, M.E., Jompa, J. and Smith, D.J., 2022. HydroMoth: Testing a prototype low‐cost acoustic recorder for aquatic environments. Remote Sensing in Ecology and Conservation. doi:

Lamont, T.A., Williams, B., Chapuis, L., Prasetya, M.E., Seraphim, M.J., Harding, H.R., May, E.B., Janetski, N., Jompa, J., Smith, D.J. and Radford, A.N., 2022. The sound of recovery: Coral reef restoration success is detectable in the soundscape. Journal of Applied Ecology, 54: 742-756. doi:

Williams, B., Chapuis, L., Gordon, T.A. and Simpson, S.D. Low-cost action cameras offer potential for widespread acoustic monitoring of marine ecosystems. 2021. Ecological Indicators. 129: 107957. doi: 10.1016/j.ecolind.2021.107957

Mahesh, R., Saravanakumar, A., Thangaradjou, T., Solanki, H.U., Raman, M. and Williams, B. Seasonal and spatial variations of mesozooplankton energy transfer efficiency determined using remotely sensed SST and Chl-a in the Bay of Bengal. Regional Studies in Marine Science. 2020. 40: 101482. doi: 10.1016/j.rsma.2020.101482

Media engagement

Newspaper articles: Forbes; The Times; Reuters; South China Morning Post, EuroNews,  
TV: 3sat Nano
Podcast appearances: Wall Street Journal; NiceGenes!
Radio interviews: The World US public radio. The Times Radio. BBC: NEWCASTLE Live, 3CR Live, WM Live, H&W Live, BERKSHIRE Live (Dec 2021). FM4 Austria.