Data Intensive Science Translation Fellow
Lead Research Organisation:
Durham University
Department Name: Physics
Abstract
The aim of this STFC Innovation Fellowship is to translate expertise developed as part of the astronomy research programme at Durham University into applications in industry. Durham Astronomy represents one of the biggest research efforts in extra-galactic astronomy in Europe, with world leading expertise in the simulation of cosmic structure formation, wide-field galaxy surveys and observations of the high redshift Universe. To date there has been little transfer of the research skills and methodologies developed in the academic research program into other sectors which face similar problems and which could benefit from techniques and approaches we have developed.
The proposal focuses on innovation transfer in three areas: i) image analysis, ii) multi-parameter model optimisation and iii) techniques for processing and mining large and sometimes incomplete datasets.
We have identified three diverse industrial partners who can potentially utilize the research expertise developed in Durham Astronomy: i) Kromek, ii) Atom Bank and iii) Modus.
The Fellow will be based in Durham University and will be seconded to the industrial partners, and will have university and industry mentors.
This proposal cuts across academic disciplines and research council support at Durham, building new collaborations with experts in image analysis from the Department of Computer Science and in multi-parameter model optimisation and model emulation from the Department of Mathematical Sciences.
The proposal focuses on innovation transfer in three areas: i) image analysis, ii) multi-parameter model optimisation and iii) techniques for processing and mining large and sometimes incomplete datasets.
We have identified three diverse industrial partners who can potentially utilize the research expertise developed in Durham Astronomy: i) Kromek, ii) Atom Bank and iii) Modus.
The Fellow will be based in Durham University and will be seconded to the industrial partners, and will have university and industry mentors.
This proposal cuts across academic disciplines and research council support at Durham, building new collaborations with experts in image analysis from the Department of Computer Science and in multi-parameter model optimisation and model emulation from the Department of Mathematical Sciences.
People |
ORCID iD |
Carlton Baugh (Principal Investigator) |
Publications
Walker J
(2023)
A mixed-method approach to determining contact matrices in the Cox's Bazar refugee settlement.
in Royal Society open science
Baugh C
(2020)
Sensitivity analysis of a galaxy formation model
in Monthly Notices of the Royal Astronomical Society
Description | The Data Innovation fellow helped to translate ideas from industry to academia (sensitivity testing of models) and also helped to analyse data on the vital signs of premature babies with NHS South Tees |
Exploitation Route | Improved treatment of neonates |
Sectors | Healthcare |
URL | https://www.sciencedirect.com/science/article/abs/pii/S0300957223003416 |
Description | The analysis of neonate data from NHS South Tees will help with the care of premature babies. |
First Year Of Impact | 2023 |
Sector | Healthcare |
Description | Atom Bank |
Organisation | Atom Bank |
Country | United Kingdom |
Sector | Private |
PI Contribution | working in partnership with Atom Bank on sensitivity analysis modelling |
Collaborator Contribution | hosting data innovation fellow; access to bank models |
Impact | none yet |
Start Year | 2018 |
Description | Kromek |
Organisation | Kromek Group plc |
Country | United Kingdom |
Sector | Private |
PI Contribution | Investigation of using scans to detect security threats |
Collaborator Contribution | Hosted the innovation fellow; provided access to proprietary data |
Impact | none yet |
Start Year | 2018 |
Description | Partner visit |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | Discussion of opportunities for knowledge transfer |
Year(s) Of Engagement Activity | 2019 |