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.
Goals
The goals of the group are to
- Disseminate information in energy and environment topic areas through seminars, workshops, and scientific publications
- Encourage collaboration between group members within this Department and help coordinate interdisciplinary initiatives across University departments.
- Provide mentoring to students (Part II, III, MPhil, and students in the AI4ER and Sensors Doctoral Training Centres)
- Create an entity that can attract external funding and donations.
- Gather equipment and laboratory space required (e.g. sensors, drones)
- Provide guidance to the Teaching Committee on Computer Science Tripos courses relevant to energy and environment.
- Contribute to the development of relevant undergraduate and graduate courses within the University.
- Have a measurable impact on tools and techniques for de-risking our future.
Membership
- Faculty members in the Department for Computer Science and Technology
- Postdocs, PhDs, Lab Visitors and Master’s students primarily from the Department for Computer Science and Technology and other departments, as appropriate
Seminars
- Details at talks.cam
- Recordings from the EEG seminar series are available to watch online (link)
- We thank the Institute of Computing for Climate Science for their sponsorship of this series.
Lent 2023
|
Date |
Title of presentation |
Speaker name |
Affiliation |
|
January 20 |
Quantifying changes in Above Ground Biomass in degraded and restored forests: Challenges & opportunities | Charlotte Wheeler |
Cambridge |
|
January 27 |
Machine Learning in Climate Action |
David Rolnick |
McGill |
|
February 3 |
The value of high resolution remote sensing to understand forests | Emily Lines |
Cambridge |
|
February 10 |
Ecovisor: A Virtual Energy System for Carbon-Efficient Applications |
David Irwin |
U. Mass Amherst |
|
February 17 |
Research Avenues for Net-Zero Carbon Cloud Datacenters | Fiodar Kazhamiaka | Microsoft |
|
February 24 |
CityLearn: An OpenAI Gym Framework for Grid-Interactive Buildings |
Zoltan Nagy |
U. Texas Austin |
|
March 3 |
TBA | Madeline Lisaius | Cambridge |
| March 10 | New framework for carbon offsets in global drylands | Adam Pellegrini | Cambridge |
Affiliated centres
- Cambridge Centre for Carbon Credits (4C)
- Cambridge Conservation Research Institute (UCCRI)
- Institute of Computing for Climate Science (ICCS)
- Centre for Doctoral Training in the Application of AI to Environmental Risks (AI4ER)
- Centre for Doctoral Training in Sensor Technologies for a Healthy and Sustainable Future
- Centre for Earth Observation
- Energy Interdisciplinary Research Centre
News
- October 2022: Prof. Anil Madhavapedd's book Real World OCaml published
- 19th July 2022: EEG group launches
- 15th July 2022: Emily Shuckburgh's Climate Change briefing to MPs
