CDT student case studies

EPSRC CDT in Cloud Computing for Big Data

CDT students collaborate cross-cohort on patient wearable device research

Peter Michalak (2014 Cohort) and Lauren Roberts (2015 Cohort)

Whilst PhD theses must be the candidate’s own work, the CDT often clusters students with complementary skills to tackle important problems from a range of research perspectives.

Two students from different intakes are researching how wearable devices can transform patient management for a range of conditions, including diabetes: Lauren Roberts, whose background is in mathematics; and Peter Michalak, with a first degree in Computer Science.

The CDT’s intake mainly consists of students with a background in either Mathematics or Computer Science. After training them in scaleable big data analytics and business they move on an individual project which allows them to explore new ideas and apply them to real-world problems.

As is often the case, no one field has the knowledge that is needed to overcome the challenges, and so Peter is focused on designing the real-time IoT system needed to process the data produced by the wearable, and Lauren on the online statistical methods needed to predict the future condition of the patient.

To ensure that the students’ work addresses the key healthcare issues, the multi-disciplinary supervisory team is made up of Professor Mike Trenell of Newcastle Medical School – a clinical expert in how activity influences diabetes – as well as a Mathematician (Dr. Sarah Heaps) and a Computer Scientist (Professor Paul Watson).

Working in a multi-disciplinary team is exciting for the students and staff, and creates the critical mass of ideas, perspectives and methods needed to translate the promise of data analytics in to results that will lead to a real improvement in the lives of the growing numbers of people in the UK suffering from diseases such as diabetes.

 

 

A digital economy network for PhD students in CDTs funded by EPSRC

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