Dr Benno Simmons

About me:

**Full details can be found on my lab website**

My research sits at the intersection of AI, technology, ecology and conservation. I develop methods for using AI to count nature at scale—and to make those counts trustworthy enough to act on. I do this because conservation depends on knowing where species are, how abundant they are, and whether their populations are declining or recovering, yet for much of biodiversity we still lack even basic monitoring data.

I work with monitoring technologies, such as camera traps and acoustic sensors, using AI to turn large volumes of images and sounds into insights for conservation decision making.

A major focus of my research is making these systems reliable and safe. Biodiversity presents unusual challenges for AI: most species have little training data, models may encounter species they have never seen before, and environmental conditions vary enormously across space and time. My research embraces these ecological realities, developing AI that is designed for the complexity, uncertainty and variability of the natural world.

Ultimately, my goal is to help build a new generation of trustworthy biodiversity monitoring systems that can provide the robust evidence needed to understand ecological change, evaluate conservation action and support better decisions for nature.

If you’re interested in these topics, or anything else that combines AI and ecology or conservation, please do get in touch.

Full details of my publications can be found on my lab website or Google Scholar.

Office hours: Wednesdays 12-1pm; Thursdays 2-3pm

Qualifications:

• PhD Zoology, University of Cambridge
• MRes, Imperial College London
• BA (Hons), University of Oxford

Career:

• 2023 - present: Lecturer in Ecological Data Science, University of Exeter
• 2020 - 2023: Research Fellow, University of Exeter
• June 2019 - December 2019: Postdoctoral Research Associate, University of Sheffield
• 2015-2019: PhD Student, University of Cambridge