Computer Science KTP Case Studies

From robotics to machine learning, the University of Birmingham is breaking new ground in the theory and practice of computational systems and their applications. Below are some examples of Knowledge Transfer Partnerships which have translated this expertise into innovative solutions for our company partners.


Designing a distributed system for performance and compliance monitoring

A Knowledge Transfer Partnership (KTP) between the University of Birmingham and BT has helped the Company to advance the monitoring capabilities of its communication procedures with a view to transforming its service delivery systems.

BT is one of the world's leading providers of communications solutions serving customers in Europe, America and Asia Pacific. Its principal activities include networked IT services, local, national and international telecommunications services, and higher-value broadband products and services. BT serves over 18 million business and residential customers, and provides network services to other licensed operators.

Under Dr Behzad Bordbar, Lecturer in the School of Computer Science at the University of Birmingham, the partnership was able to design and implement a distributed system for performance and compliance monitoring in BT's service oriented computer structures.

Professor Ben Azvine

Head of Security Research, BT

“The KTP with the University of Birmingham will help us to deal with faults and problems in near real-time and identify root causes to problems so that we can avoid recurrences in the future. This will enhance our competitiveness in the market and consolidate our role as an innovative leader in the industry.”


Cogitare Ltd.

New approaches to modelling rail capacity

The United Kingdom’s rail network is busier than ever. There are 40% more passenger journeys than there were 10 years ago, and 60% more freight. Over the next 30 years freight demand is expected to rise 140%, and passenger demand will more than double. While investment into Britain’s infrastructure will offset some of this, finding efficiencies in the existing network will help to make busy lines more pleasant for travellers.

In 2014 the University of Birmingham and Cogitare Ltd embarked upon an ambitious Knowledge Transfer Partnership (KTP) to develop innovative methods for measuring and modelling rail capacity. Cogitare, a young and dynamic niche consultancy operating out of South Bank Technopark in London, would work with the Birmingham Centre for Railway Research and Education (BCRRE) to develop software that could not only extract additional benefits from existing lines but also help rail operators to know where they should invest their money.

The KTP has helped to develop an innovative new approach to railway modelling, whereby customer experience becomes a key factor in deciding what services to run. For example, a fully-packed train may get the most passengers from a to b in a short space of time, but many commuters would be willing to trade a 5 minute delay if they could guarantee a seat. Or a network that would favour direct journeys over those with two or more stops.

For Cogitare, a company without the in-house capacity to develop this knowledge, KTP provided them with a proven framework for carrying out an R&D project. Funding provided by Innovate UK and the Rail Safety and Standards Board (RSSB) went towards the salary of a recent graduate, Bibil Paramattathil, who dedicated 2 years to this project. Bibil was assisted by academic oversight from Dr Stuart Hillmansen and Professor Clive Roberts of the University of Birmingham.

Larry Fawkner

Director, Cogitare Ltd.

“Business success is more and more about better knowledge and technology. Bringing together different minds and knowledge through the KTP and harnessing Birmingham’s intellectual force with our experience is allowing us to develop new, highly-innovative products which we would not have been able to do without the KTP, and is at the heart of our future business success.”


The Supplies Group (TSG)

Developing a competitive edge through Machine Learning

The Supplies Group (TSG), an internet retailer, acquires all its customers through online marketing, mostly at a financial loss, with the hope of selling other products to them in the future. As the Company did not know, or understand, the profile of the most valuable customers they felt that the return on their investment in customer acquisition and retention was not being maximised.

Working with researchers from the University's School of Computer Sciences, led by Dr Peter Tino, the Company embarked on a KTP project which developed methods to represent customers based on patterns of historical sales data and to predict their Life Time Value (LTV). Algorithms were developed to identify the most important product families with the potential to indicate customers with high future profitability.

The KTP has had considerable impact with TSG having recruited 3 postgraduates from the University to take forward, and build on, the results of the project, and an expectation that a further 3 posts will be created. Furthermore TSG is predicting a £2.5M pa increase in customer acquisition revenue and a 15% increase in existing customer LTV which will contribute to an additional £2M of potential annual revenue growth. A further two EPSRC (Engineering and Physical Sciences Research Council) funded projects have also evolved from this project.

Noah Gresham

Director, The Supplies Group

“The project outputs will give TSG a tangible competitive advantage in online customer acquisition efforts. The work will allow us to identify customers of high value and target our marketing budget to maximise acquisition of such customer groups while minimising exposure to low value customers.”


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