Biography
David Wallom is a Professor in Informatics and Associate Director – Innovation of the Oxford e-Research Centre, where he leads two separate research groups, Energy and Environmental ICT, and Advanced e-infrastructure & Cloud Computing.
He has led over 55 research projects in areas such as Cloud utilisation, Cybersecurity, Smart Energy Grids, Research Data Management, Green IT, ICT Security and Institutional Repositories. He is a member of the GCHQ recognized Academic Centre of Excellence in Cyber Security and the UK Space Agency Ground segment Advisory Group.
David is the academic Board Member of the HEFCE Institute for Environmental Analytics, Chair of the Scientific Advisory Board for the Norweigan Information for Action e-Science Centre and a member of the SAB for the NEGI Tools for Investigating Climate Change at High Northern Latitudes (eSTICC) & Ensemble-based Methods for Environmental Monitoring and Prediction (EmblA) centres. He is also Co-Editor in Chief of the Elsevier journal SoftwareX.
Most Recent Publications
Digitalization opportunities to enable local power system transition to net-zero
Digitalization opportunities to enable local power system transition to net-zero
A comparative climate-resilient energy design: Wildfire Resilient Load Forecasting Model using multi-factor deep learning methods
A comparative climate-resilient energy design: Wildfire Resilient Load Forecasting Model using multi-factor deep learning methods
Ensemble of global climate simulations for temperature in historical, 1.5 ??C and 2.0 ??C scenarios from HadAM4
Ensemble of global climate simulations for temperature in historical, 1.5 ??C and 2.0 ??C scenarios from HadAM4
Energy consumption in higher education buildings: bridging the performance gap using digital twin technology
Energy consumption in higher education buildings: bridging the performance gap using digital twin technology
Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network
Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network
Research Interests
David has a diverse set of research interests with research projects either ongoing or recently completed in all of them.
Advanced e-Infrastructure and Cloud Computing
- Cloud Computing technology and systems
- Cloud/e-infrastructure Policy and Education
- Cyber-security
- IoT
- Active Research Data Management
- Volunteer Computing & Desktop Grids
Energy and Environmental Informatics
- Energy Services
- Smart Metering
- Ecosystem Services
- Citizen Science
- Climate Change Impact
David is the Founding Editor in Chief of the Elsevier SoftwareX journal.
Current Projects
CyberWatching (EC H2020, Co-I)
Understanding the EC and EU-27 Cybersecurity R&I landscape
Data Management in intel (InnovateUK KTP, PI)
Transforming an information led SME towards a total information management solution.
Drivers Of Change In mid-Latitude weather Events (NERC, Co-I)
Developing the next higher resolution global climate model for CPDN.
Extreme Weather (The Nature Conservancy, CoI)
Understanding the effect of anthropogenic climate change on the Amazonian basin and strategies for mitigation of effects.
Forest Mortality and Environmental Change (US NIFA, Co-I)
Connecting climate change to economic effects in the NW US timber industry.
Globally Observed Teleconnections and their role, (Belmont/NERC, Co-I)
Understanding the long term connections between climate events and weather.
Long Term Undulations versus secular change in Chinese Climate, LOTUS-China (MetOffice, Co-I)
Developing the science to support climate services in China.
Trusted Public Cloud (InnovateUK KTP, PI)
Creating cryptographically secure public cloud systems.
World Weather Attribution (Climate Central inc, Co-I)
Generating near to real time attribution statements on the link between extreme weather events and climate change.
Most Recent Publications
Digitalization opportunities to enable local power system transition to net-zero
Digitalization opportunities to enable local power system transition to net-zero
A comparative climate-resilient energy design: Wildfire Resilient Load Forecasting Model using multi-factor deep learning methods
A comparative climate-resilient energy design: Wildfire Resilient Load Forecasting Model using multi-factor deep learning methods
Ensemble of global climate simulations for temperature in historical, 1.5 ??C and 2.0 ??C scenarios from HadAM4
Ensemble of global climate simulations for temperature in historical, 1.5 ??C and 2.0 ??C scenarios from HadAM4
Energy consumption in higher education buildings: bridging the performance gap using digital twin technology
Energy consumption in higher education buildings: bridging the performance gap using digital twin technology
Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network
Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network
DPhil Opportunities
I am interested in supporting DPhil applications by those interested in any of the areas of my research, but most particularly in those topics which fall within my definition of Energy and Environmental Informatics as well as cloud computing technologies.
Most Recent Publications
Digitalization opportunities to enable local power system transition to net-zero
Digitalization opportunities to enable local power system transition to net-zero
A comparative climate-resilient energy design: Wildfire Resilient Load Forecasting Model using multi-factor deep learning methods
A comparative climate-resilient energy design: Wildfire Resilient Load Forecasting Model using multi-factor deep learning methods
Ensemble of global climate simulations for temperature in historical, 1.5 ??C and 2.0 ??C scenarios from HadAM4
Ensemble of global climate simulations for temperature in historical, 1.5 ??C and 2.0 ??C scenarios from HadAM4
Energy consumption in higher education buildings: bridging the performance gap using digital twin technology
Energy consumption in higher education buildings: bridging the performance gap using digital twin technology
Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network
Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network