S. Keshav
I’m the Robert Sansom Professor of Computer Science at the Department of Computer Science and Technology, University of Cambridge, and a Professorial Fellow at Fitzwilliam College. I’m also a Fellow of the Royal Society of Canada, ACM, and IEEE.
We’re in a race against time. Climate change and biodiversity loss threaten all ife on earth, yet we have unprecedented computational and observational capabilities. My work is driven by the conviction that computer science can—and must—be a force for planetary good.
I love interdisciplinary research, building systems that scale, training the next generation of students, and creating open tools.
Note: Keshav is my given name and here is how my name is pronounced: Srinivasan Keshav
Current projects
A global, open, 10-meter resolution foundation model for Earth observation. We’re making planetary-scale environmental monitoring accessible to anyone with a laptop. TESSERA processes satellite imagery to detect deforestation, monitor ecosystems, and track land use changes. It’s being used by conservation organizations, researchers, and governments worldwide.
The Tessera Embeddings Explorer is an interactive tool for exploring TESSERA embeddings. Users can create small (5 km × 5 km) viewports to browse false-colour embeddings alongside Open Street Map and RGB satellite imagery, set labels for locations, and find locations with similar embeddings.
I’m writing a free, open-source graduate textbook. I’m using Quarto, VSCode, and modern collaborative tools to make it not just a book, but a living hub for the energy informatics community.
More details on what I’m currently working on.
Thumbnail biography
I started as a researcher in computer networking in 1988, working on topics such as congestion control, packet scheduling, disconnection tolerant networking, and system architecture. Around 2010, I had a realization: the most important problems facing humanity aren’t about buildingfaster networks—they are about sustainability. Since then, I’ve worked on reducing carbon footprints in energy generation, transportation, and buildings, and for the past five years, my focus has been on using satellite data and machine learning to understand and protect Earth’s ecosystems. My overall vision is to use computational thinking and computing systems to solve problems that matter.
Recent highlights
- I’ve released the first chapter of my free and open-source graduate textbook An Introduction to Energy Informatics. This chapter summarises the power grid.
- Tutorial on self-supervised learning at ACM eEnergy 2025. Slides here
- Public lecture: “Is there hope for the climate?”