<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/2B896E0B-6E71-4B9D-85B0-D8A509A6CD25" ns1:id="2B896E0B-6E71-4B9D-85B0-D8A509A6CD25"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/A59DCE2E-7CCA-470B-BEB7-9F399A8E6005" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/47E41D4D-B81F-4FC0-B3E8-F9B975030E79" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/47E41D4D-B81F-4FC0-B3E8-F9B975030E79" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-04-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/EA665395-CA4A-45E5-B592-F0FBE62EFCB3" ns1:rel="FUND" ns1:start="2022-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10045270</ns2:identifier></ns2:identifiers><ns2:title>Predictive modelling of wellbeing in high growth companies</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Grant for R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Lumien is a wellbeing analytics platform that measures where individuals &amp;amp; populations struggle with their mental and physical wellbeing at home and at work and offers support to help individuals, managers and organisations understand and manage problems.

We are currently using machine learning to move towards a pro-active model. Identifying when individuals or populations may begin to struggle and suggesting small adjustments to reduce the negative impact of mental wellbeing to both individuals and teams before it occurs.

This project aims to improve the dimensionality of our data, therefore allowing more targeted analysis of mental wellbeing across populations.</ns2:abstractText></ns2:project>