Imperial College London


Faculty of Natural SciencesDepartment of Mathematics

Research Postgraduate



s.sethi16 CV




Electrical EngineeringSouth Kensington Campus





PhD student across the Applied Mathematics, Design Engineering and Tropical Forest Ecology departments. 

I aim to develop an end-to-end system for real-time continuous bioacoustic monitoring of ecosystems. This has included developing and deploying robust acoustic monitoring units to the field, and interpreting the time series data to quantify the biodiversity of a region.

A network of these sensors is deployed in the Stability of Altered Forest Ecosystems (SAFE) Project, located in the tropical rainforests of Borneo, to help understand the effect of changing land use upon local wildlife. You can listen to audio from our acoustic monitoring network at the SAFE Acoustics website.

I am also involved with work developing tools and approaches for cross-disciplinary highly comparative time-series analysis (hctsa), including the analyses behind the CompEngine website.

Member of the Science and Solutions for a Changing Planet Doctoral Training Program (SSCP DTP). 

Visiting tutor for Innovation Design Engineering (IDE) M.A. / M.Sc. joint course with Royal College of Arts.



Lubba CH, Sethi SS, Knaute P, et al., 2019, catch22: CAnonical time-series CHaracteristics, Data Mining and Knowledge Discovery, Vol:33, ISSN:1384-5810, Pages:1821-1852

Sethi S, Ewers R, Jones N, et al., 2018, Robust, real-time and autonomous monitoring of ecosystems with an open, low-cost, networked device, Methods in Ecology and Evolution, Vol:9, ISSN:2041-210X, Pages:2383-2387

Sethi SS, Zerbi V, Wenderoth N, et al., 2017, Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain, Chaos, Vol:27, ISSN:1054-1500

More Publications