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Centre for Digital Built Britain

 
Read more at: Capturing changing activity in London as lockdown eases

Capturing changing activity in London as lockdown eases

3 July 2020

Cambridge researchers are part of a collaborative project tasked with developing models, infrastructure and machine learning algorithms for capturing mobility, transportation and traffic activity in London, as the COVID-19 pandemic lockdown eases. Project Odysseus , led by The Alan Turing Institute , aims to better...

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Dr Farhad Huseynov

Research background

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Gabriel Martin Hernández

Research background

PhD. Gabriel Martin was a Predoctoral Research Associate with the Hyperspectral Computing Laboratory Cáceres (Spain) and Postdoctoral Researcher in "Instituto de Telecomunicaçoes" Lisbon, Portugal. His research interests include remote sensing image processing, specifically the areas of hyperspectral unmixing and hyperspectral compressive sensing, as well as the efficient processing of remote sensing images in High Performance Computing architectures such as GPUs.

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Dr Rohit Verma

Research background

My primary area of research has been in the field of sensor data collection and analysis obtained from multi-modal sources. In my CDBB project, I am working on developing an architecture for real-time analysis of the data being generated by sensors deployed on a citywide scale.

CDBB projects involved with

West Cambridge Digital Twin Research Facility

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Dr Matthew Danish

Research background

Matthew Danish is a Research Associate within the Networks and Operating Systems group of the Systems Research Group in the Department of Computer Science and Technology. He is interested in systems verification, sensor networks, machine learning, infrastructure and the built environment.

CDBB projects involved with

West Cambridge Digital Twin

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Read more at: Network for Ontologies (FOuNTAIN)

Network for Ontologies (FOuNTAIN)

This research network aims to take a user-centric approach to interacting with information, from search and retrieval to browsing and exploration, and to consider the following three dimensions: (1) the lifecycle of information, from its creation, delivery, capture, preservation, management...

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Read more at: Visualising the Future: Big Data and the Built Environment

Visualising the Future: Big Data and the Built Environment

Building on four years of material generated by the Cambridge Forum for Sustainability and Environment, this report examines the future use of big data in the built environment. Experts from academia, government and private companies were invited to join monthly discussions in the Forum over four...

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Read more at: Crowdsourcing Data in Mining Spatial Urban Activities

Crowdsourcing Data in Mining Spatial Urban Activities

This project aims to understand how check-in data from social media is distributed around Cambridge and what kinds of spatial segmentation can be identified. It validated the social media data on urban segregation using observation and questionnaires. We conducted pilots at Cambridge in the UK and...

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Vladimir Vilde

Research background

Prior to Cambridge, Vladimir did a Msc in physics at the University of Namur (Belgium) where he started to work on low-cost optical system for the monitoring of precious manuscripts. He then pursues a doctoral degree at University College London in material science for art conservation. During this time, he developed more accessible imaging methodologies for the monitoring of painting collection managed by English Heritage as well as working on more comprehensive monitoring and data analysis of environmental condition in historical houses.

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Paul Fidler

Research background

Paul joined the Department of Engineering in 1995, initially to work on the development of a yield-line analysis program for concrete bridges. In recent years, Paul's research has been on using new sensing technologies such as wireless sensors or fibre-optic strain measurements for civil infrastucture assets.

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