Imperial College London

Dr Sarab Sethi

Faculty of Natural SciencesDepartment of Life Sciences

Lecturer in Ecosystem Sensing







Translation & Innovation Hub BuildingWhite City Campus





I lead the interdisciplinary Ecosystem Sensing research group in the Department of Life Sciences under the university's Imperial-X AI initiative. We create new sensor systems and data analysis approaches to build next-generation biodiversity monitoring systems.

We focus on acoustic monitoring of natural environments, developing novel real-time sensing systems ( and AI to extract ecological insight at scale from audio data.

I have led the deployment of large-scale autonomous biodiversity monitoring networks in Borneo’s tropical forests ( as well as across the entire span of Norway ( Applications of my work include conservation, ecology, pest control, supply chain transparency, and more.

Google Scholar profile

PhDs and Postdoctoral fellowships

There are currently no open positions in the lab. However, if you are interested in applying for an externally funded PhD or postdoctoral fellowship to be hosted in our lab, please do get in touch.



Cretois B, Bick IA, Balantic C, et al., 2024, Snowmobile noise alters bird vocalization patterns during winter and pre-breeding season, Journal of Applied Ecology, Vol:61, ISSN:0021-8901, Pages:340-350

Sethi SS, Bick A, Ewers RM, et al., 2023, Limits to the accurate and generalizable use of soundscapes to monitor biodiversity, Nature Ecology and Evolution, Vol:7, ISSN:2397-334X, Pages:1373-1378

Ross SRP-J, O'Connell DP, Deichmann JL, et al., 2023, Passive acoustic monitoring provides a fresh perspective on fundamental ecological questions, Functional Ecology, Vol:37, ISSN:0269-8463, Pages:959-975

Norman DL, Bischoff PH, Wearn OR, et al., 2023, Can CNN-based species classification generalise across variation in habitat within a camera trap survey?, Methods in Ecology and Evolution, Vol:14, ISSN:2041-210X, Pages:242-251

Cretois B, Rosten CM, Sethi SS, 2022, Voice activity detection in eco-acoustic data enables privacy protection and is a proxy for human disturbance, Methods in Ecology and Evolution, Vol:13, ISSN:2041-210X, Pages:2865-2874

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