Natural resources and forests - staff

Academic Staff

David Coomes

Department of Plant Sciences

Themes and techniques: Agriculture, biodiversity, environmental hazards, forest, space, artificial intelligence, data science, machine learning, modelling, remote sensing

Nik Cunniffe

Department of Plant Sciences

Themes and techniques: Theoretical and computational epidemiology (forests), modelling

Jennifer Gabrys

Department of Sociology 

Themes and techniques: Air quality, forests, digital social research, interviews, participation

Theo Hacking

Cambridge Institute for Sustainability Leadership

Themes and techniques: Decision support tools for sustainability/ sustainable development, including social and environmental impact assessment and sustainability assessment

Richard Harrison

Department of Earth Sciences

Themes and techniques: Mineral sciences, nanopaleomagnetism (natural resources)

Marian Holness

Department of Earth Sciences

Themes and techniques: Petrology: Igneous, Metamorphic and Volcanic studies (natural resources), petrographic techniques coupled with geochemical analysis to decode rock history

Srinivasan Keshav

Department of Computer Science and Technology

Themes and techniques: Buildings, energy, forests, artificial intelligence, data science, machine learning, modelling, remote sensing

Emily Lines

Department of Geography

Themes and techniques: Forests, remote sensing

Adam Pellegrini

Department of Plant Sciences

Themes and techniques: Forests, environmental hazards and disaster risk, modelling

Emilie Ringe

Department of Earth Sciences

Themes and techniques: Multi-Scale, multi-dimensional imaging of natural and synthetic materials (natural resources)

Nina Seega

Cambridge Institute for Sustainability Leadership, Centre for Science and Policy

Themes and techniques: Financial risk management, sustainable finance

Andrew Tanentzap

Department of Plant Sciences

Themes and techniques: Natural resources, artificial intelligence, data science, machine learning, modelling, remote sensing

Adrian Weller

Department of Engineering, Centre for Science and Policy, Alan Turing Institute

Themes and techniques: Machine learning and artificial intelligence, their applications and their implications for society