Lancaster University - Equipment Account
Lead Research Organisation:
Lancaster University
Department Name: UNLISTED
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
Publications
Yates K
(2016)
Minimum density hyperplanes in the feature space
Winter H
(2016)
Modelling Heatwaves in Central France: A Case-Study in Extremal Dependence
in Journal of the Royal Statistical Society Series C: Applied Statistics
Winter H
(2016)
kth-order Markov extremal models for assessing heatwave risks
in Extremes
Winter H
(2016)
Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia
in The Annals of Applied Statistics
Williamson SF
(2017)
A Bayesian adaptive design for clinical trials in rare diseases.
in Computational statistics & data analysis
Turner Lisa
(2016)
Bayes Linear Methods for Large-Scale Network Search
in arXiv e-prints
Sharkey P
(2016)
A Poisson process reparameterisation for Bayesian inference for extremes
in Extremes
Rohrbeck Christian
(2016)
Bayesian Spatial Monotonic Multiple Regression
in arXiv e-prints
Randell D
(2016)
Bayesian inference for nonstationary marginal extremes
in Environmetrics
| Description | This capital equipment award funded video-conferencing and video-enabled lecture theatre infrastructure and well as high performance research machines. This equipment helps facilitate the research development and training of the STOR-i CDT students. The key outcomes of the award are best measured through the publications from the students, their industrial engagement, and the quality of careers that they progress to. The industrial partners they have undertaken their PhD projects with are list below. Papers are listed separately. To give an indication of STOR-i's track record for student destinations the following, employing organizations include: British Airways, Dunnhumby, Shell, EDF Energy, Exient (then to Sega), FeatureSpace, JBA, Lubrizol, Summit Media and DrMemory (a local start up company), Sporting Data (a start up company). Several have also proceeded to post-doctoral research positions, with two currently appointed to lectureships. |
| Exploitation Route | We are delighted that our vision for STOR-i students to take up leadership roles in Statistics and OR is starting to be realised. The overwhelming majority of the above industry positions explicitly use specific research skills developed in the PhD, together with broader generic Statistics and OR and career skills developed throughout STOR-i training. We are also beginning to see the STOR-i Fellowship programme providing a bridge to academic career paths. PhD Projects have been with Aimia, ATASS, BT, DSTL, EDF, Jansen, JBA, Met Office, NNL, Roche, Rolls Royce, Shell, Sparx, with about half of these companies providing multiple projects. |
| Sectors | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Energy,Manufacturing, including Industrial Biotechology |
| Description | The key impacts of the award come through the CDT students research papers and impact on their projects with industry listed elsewhere. Given the nature of the equipment purchased its direct impact is best explained by showing how it influences the working practice of the CDT students. STOR-i students regularly use the high quality video-conferencing facilities to support their supervision as all students have either an international academic partner or an industrial partner providing co-supervision. Developing such virtual communication and team-working skills is invaluable for tomorrow's research leaders, as many can expect to have future careers working in 'virtual' teams. The audio-visual equipment substantially enhances our training programme. It enables both video-lectures for our international masterclasses and seminars and the capture of training sessions. The ability to transmit lectures reliably from international speakers enhances the opportunity for STOR-i students to learn from the world's leading researchers who may not be able to visit the Centre. This has been particularly valuable given international travel patterns during the pandemic. The vast majority of the STOR-i students are using our advanced high performance research machines to undertake large-scale optimisation, simulation and computationally intensive data analysis. This has facilitated a huge amount of research that now underpins impacts arising in a range of sectors: from supermarket retailers to telecoms, offshore energy to nuclear decommissioning. Specific examples include: 1. the work of students within the Centre developing novel anomaly detection methods. These are being used by BT to provide data-driven insights that help operate and maintain the UK's internet infrastructure; 2. work on inference for extreme earthquake magnitudes accounting for a time-varying measurement process, which is now starting to have impact in the oil and gas industry. Please see individual student outcomes for further details. |
| First Year Of Impact | 2018 |
| Sector | Agriculture, Food and Drink,Digital/Communication/Information Technologies (including Software),Education,Energy,Environment,Financial Services, and Management Consultancy,Healthcare,Government, Democracy and Justice,Pharmaceuticals and Medical Biotechnology,Retail,Transport |
| Impact Types | Societal,Economic |