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Department of Computer Science and Technology

 

Energy and Environment Group (EEG)

The Energy and Environment Research Group applies computer science to address renewable energy integration, energy demand reduction, and the assessment and management of environmental impact (e.g. climate change, biodiversity loss, deforestation) from anthropogenic activities.

We operate in an interdisciplinary manner, collaborating with climate scientists, ecologists, engineers, lawyers, regulators, and economists, and conducting wide engagement with external partners to effect evidence-based outcomes.

Goal

Our primary goal is to have a measurable impact on tools and techniques for de-risking our future. To do so, we share recent advances at the intersection of computer science, energy, and the environment through seminars, workshops, and scientific publications. We also help form collaborations between group members to coordinate interdisciplinary initiatives across University departments. 

Membership

EEG members are, in the first instance, faculty members in the Department for Computer Science and Technology and their students. We also invite membership from Postdocs, PhDs, Lab Visitors and Master’s students primarily from other departments, as appropriate.

Seminars

A list of talks for the current term can be found below; talks from prior terms are linked to this page. Seminar details can also be found at Talks.cam. Recordings from the EEG seminar series are available to watch online. We thank the Institute of Computing for Climate Science for their sponsorship of this series.


Partners


Upcoming seminars

Lent term

  • 31Jan
    Toby Kiers, SPUN, Vrije Universiteit, Amsterdam

    *Abstract*

    Mycorrhizal fungi form complex living networks that connect plants. These fungal networks supply nutrients to the Earth’s plant communities in exchange for plant carbon. As a result, mycorrhizal fungi draw down ~13 billion tons of CO2 per year into the soil annually, equivalent to ~1/3 of global anthropogenic energy-related emissions. We have developed an imaging robot that allows us to now study the dynamics of nutrient flows through mycorrhizal networks. Our past work has shown that fungi control carbon and nutrient flow with surprising precision, allowing them to resolve complex supply-chain trade-offs. These trade algorithms have been shaped by natural selection for hundreds of millions of years. A better understanding of these design principles can help us develop effective ecological interventions that rely on fungi to draw more carbon below ground. 

    *Bio*

    Dr. Toby Kiers is a Professor of Evolutionary Biology at the VU in Amsterdam, where her lab studies the flows of carbon and nutrients inside fungal networks. She is the co-founder,
    Executive Director, and Chief Scientist of the Society for the Protection of Underground Networks (SPUN). Kiers was named by TIME100 as an emerging leader for her work decoding fungal trade patterns, and an Explorer 50 for her work in mapping underground fungal systems across the Earth. She is the youngest scientist to ever win the SPINOZA prize – known as the ‘Dutch Nobel Prize’. Kiers won the E.O. Wilson Award for Natural History, and the Stairway to Impact Award recognizing researchers creating societal impact with their scientific results. Kiers was named by the UNas one of the 22 scientists making a difference in biodiversity research, and an ‘Innovator to Watch’ by Smithsonian Magazine.

  • 07Feb
    Frank Feng, University of Cambridge

    Abstract not available

  • 21Feb
    Cyrill Stachniss, University of Bonn

    *Abstract*

    Crop farming is essential in our society, providing food, feed, fiber, and fuel. We heavily rely on crop production, but at the same time, we need to reduce the production footprint. We aim to address this key challenge by investigating new solutions to produce crops more sustainably. We study novel technology-driven approaches to move toward sustainable crop production. Agricultural robots offer promising directions to address management challenges in agricultural fields or support plant breeding efforts through large-scale trait acquisition. For that, field robots need the ability to perceive and model their environment, predict possible future developments, and make appropriate decisions in complex and changing situations. This talk will showcase our recent developments in robotics for crop production, incorporating machine learning to support farmers in operating more sustainably and reducing some negative impacts on the ecosystem.

    *Bio*

    Cyrill Stachniss is a full professor at the University of Bonn and heads the Photogrammetry and Robotics Lab. He is also a Visiting Professor in Engineering at the University of Oxford and is with the Lamarr Institute for Machine Learning and Artificial Intelligence. Before his appointment in Bonn, he was with the University of Freiburg and ETH Zurich. Since 2010, he has been a Microsoft Research Faculty Fellow and received the IEEE RAS Early Career Award in 2013. From 2015 to 2019, he was senior editor for the IEEE Robotics and Automation Letters. He is the spokesperson of the DFG Cluster of Excellence "PhenoRob" at the University of Bonn, together with his colleague Heiner Kuhlmann. His research focuses on probabilistic techniques as well as learning approaches for mobile robotics, perception, and navigation. The main application areas of his research are autonomous service robots, agricultural robotics, and self-driving cars. He has co-authored over 300 publications and has coordinated multiple large-scale research projects on the national and European levels. Besides his university involvement, he cofounded three startups: Escarda Technologies, DeepUp, and PhenoInspect.

  • 28Feb
    Jakob Poffley, University of Cambridge

    *Abstract*

    Illegal wildlife trade is a key driver of biodiversity loss, but targeting policy to maximise disruption to trade remains a key challenge. A network approach was applied to seizure data to prioritise national action disrupting the illegal trade of elephant ivory. By simulating the removal of countries from trade, targeting groups of countries was found to be most effective due to network redundancy. Despite temporal variability, trade was highly concentrated and cessation in less than 10 countries would have disrupted 75% of trade in 2018-2020. These findings support evidence-based legislation and efficient allocation of conservation resources for tackling illegal wildlife trade.

    *Bio*

    Jakob is a PhD student in the Conservation and Development Lab (Department of Geography). His research focuses on evaluating policy for sustainable land systems, supervised by Prof. Rachael Garrett and Prof. Srinivasan Keshav. This work is supported by the Centre for Doctoral Training on Artificial Intelligence applied to the study of Environmental Risk (AI4ER CDT). Before starting his PhD, Jakob completed an MRes with AI4ER in Environmental Data Science, where he collaborated with TRAFFIC to develop data-driven tools to inform international illegal wildlife trade policy. Previously, Jakob completed an undergraduate degree in Natural Sciences at the University of Cambridge, specialising in Plant Sciences, and contributed to research on metrics for biodiversity offsetting, novel approaches to wildlife monitoring and forest ecology.

  • 21Mar
    Emilio Luz-Ricca, University of Cambridge

    *Abstract*

    Stay Tuned!

    *Bio*

    Emilio is a PhD student in the Department of Zoology at the University of Cambridge in the Conservation Science Group and the Energy and Environment Group. He is supervised by Andrew Balmford, with co-supervision from Anil Madhavapeddy and Tom Swinfield. He is also part of the AI for Environmental Risks Centre for Doctoral Training, a researcher at the Cambridge Centre for Carbon Credits, and a member of Churchill College. His research focuses on the uses of predictive modeling for biodiversity conservation, with an emphasis on quantifying species-specific responses to human disturbance.

  • 28Mar
    Jean Martina, Universidade Federal de Santa Catarina

    Abstract not available

Easter term