Submitted by Rachel Gardner on Wed, 13/01/2021 - 14:18
Srinivasan Keshav, the Robert Sansom Professor of Computer Science here, has been named the founding Vice-Chair of a new Special Interest Group on Energy set up by the Association for Computing Machinery (ACM).
SIGENERGY brings together an inter-disciplinary group of computer scientists with diverse backgrounds in sensing, modelling, optimization, control, network and systems design, and experimentation to discuss and address key challenges in future energy systems, and their impact on society.
Its Executive Committee says there is an urgent need to bring together researchers from a variety of computing disciplines to address this grand challenge. "In this context, we are pleased to announce the formation of a new ACM Special Interest Group on Energy - SIGENERGY - which will provide a forum for researchers and practitioners who use computational methods and technologies for designing and optimizing energy systems to reduce their carbon footprint."
Keshav is Vice-Chair of the inaugural Executive Committee, working alongside committee members from the Universities of Massachusetts, Columbia and Alberta, and IBM Research.
As he explains, he originally started out as a researcher in computer networking in 1988. But for the last 10 years has focused on reducing the carbon footprint of energy generation, transportation, and buildings.
"Recently, I have also worked on improving the performance of the Hyperledger Fabric blockchain so that it can be used as the foundation for highly-scalable energy systems, such as for transactive energy and renewable energy certificates," he says.
"I have also recently turned my attention to the carbon sequestration and biodiversity potential of forests, looking at both conservation and restoration."
Keshav is also Co-Director of the UKRI Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER), which is co-hosted by this Department.
AI4ER trains researchers to develop and apply leading edge computational approaches to address critical global environmental challenges by exploiting vast, diverse and often currently untapped environmental data sets. Many of its current cohort of PhD students are working on projects with supervisors here.
