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Joe Yearsley
Applied ML Lead at Kheiron Medical
Joe Yearsley is an experienced professional in the field of machine learning and artificial intelligence, currently serving as the Applied ML Lead at Kheiron Medical.12 He has been in this role since April 2020, where he oversees machine learning projects and manages the ML codebase and infrastructure.3
Career Background
Prior to his current position, Joe held the following roles:
- Machine Learning Research Engineer at Kheiron Medical (January 2017 - April 2020)1
- Senior Applied Researcher at Kheiron Medical3
Education and Affiliations
Joe Yearsley's educational background includes:
- The University of Edinburgh2
- Bury Grammar School
- PwC Talent Academy
He is also an alumnus of InfAtEd and join_ef 7.5
Location and Connections
Joe is based in London, England, United Kingdom.4 On LinkedIn, he has over 500 connections, indicating a strong professional network in his field.2
Areas of Expertise
As an Applied ML Lead, Joe's responsibilities likely include:
- ML project management
- Overseeing ML codebase and infrastructure
- Leading applied research in machine learning
His work at Kheiron Medical suggests a focus on applying machine learning techniques in the medical field, potentially for improving healthcare technologies and diagnostics.
Online Presence
Joe maintains an active online presence:
- He has a personal website: joeyearsley.co.uk3
- Twitter handle: @joeyearsley_5
- Google Scholar profile, indicating academic publications in his field6
Joe Yearsley's LinkedIn profile can be found under the username joe-yearsley-475b4b75, as mentioned in the query.
Highlights
https://lnkd.in/em2T4DNc
Sometimes the work we are doing can seem just numbers on a screen. Hearing first hand from patients & doctors on how Mia has helped them brings meaning to those numbers.
It’s great to see the NHSx AI award pay off like this, thank you Dominic Cushnan.
https://lnkd.in/exm7JFk5
Kheiron has proven technology which can help in the screening part of the pathway. With more data to be shared soon on our prospective trials.
I understand it’s not a solution which resolves all issues along the pathway but by solving parts hopefully we can improve the service.
