On 10 April at the Microsoft Centre in Brussels, a new centre was launched which will focus on the issues stemming from the intersection of technology and regulation.
The Microsoft Cloud Computing Research Centre (MCCRC) is a virtual research centre in which technology lawyers and computer scientists will work collaboratively on cutting-edge research challenges in cloud computing. MCCRC will demonstrate thought leadership in complex and difficult areas of vital importance to governments, businesses, and communities around the globe, where technology and regulation intersect.
MCCRC is a collaboration between Cambridge University’s Computer Laboratory , the Centre for Commercial Law Studies at Queen Mary University London, and the Centre for Science and Policy.
Professor Jon Crowcroft (Marconi Professor of Communications Systems, Cambridge Computer Laboratory) who leads on the Cambridge side said: "The Cloud has had a somewhat nebulous existence in terms of where it resides, both in physical but crucially, also in jurisdictional terms. Part of the attraction of pooling resources and outsourcing has been the economies of scale that this has bought to storage and computation. What MCCRC intends doing is to bring some clarity, technically and legally, to what happens where and why, and what is or should not be allowed. We're excited to combine forces with the Centre for Science and Policy, and QMUL's Cloud/Legal team to address these timely questions."
CSaP will play an important role in providing the network and support to ensure that policy makers are actively engaged throughout. MCCRC was launched at the Microsoft Centre in Brussels, the event well attended by industry and policy makers alike. Later this year, a workshop will be hosted in Cambridge to showcase initial research outcomes, invite discussion and debate, and encourage further collaboration.
Banner image from Tristan Schmurr via CC4.0
8 September 2016
This two-day symposium organised by the Microsoft Cloud Computing Research Centre (MCCRC), will explore issues of vital importance to cloud-supported machine learning.