Fellow Detail

Photo of Loïc Lannelongue
Name Loïc Lannelongue
Affiliation University of Cambridge
Department VPD Heart and Lungs Research Institute - Department of Public Health and Primary Care
Group Cardiovascular Epidemiology Unit
Research area code (I5) Health informatics
Fellowship Inauguration Year 2023
Institutional Website https://www.phpc.cam.ac.uk/people/ceu-group/ceu-research-staff/loic-lannelongue/
Website https://www.lannelongue.eu
ORCID 0000-0002-9135-1345
Google Scholar https://scholar.google.co.uk/citations?user=VRr3DlcAAAAJ
GitHub Llannelongue
Twitter Loic_Lnlg
LinkedIn loïc-lannelongue-b11046107
Interests

Green computing Sustainability Radiogenomics Computational biology

Short Biography

I am currently a Research Associate in Biomedical Data Science at the University of Cambridge. I spend half of my time leading the Green Algorithms initiative to promote more environmentally sustainable computational science and the other half thinking of ways to combine machine learning, genomics and medical imaging to better understand cardiovascular diseases.

I first studied in Paris (France) at Lycée Saint-Louis and ENSAE Paris where I earned a BSc and a French Diplôme d’Ingénieur (MSc) majoring in mathematics and statistics, with minors in theoretical physics and economics. I then earned an MSc in statistics and machine learning from the University of Oxford. I joined Cambridge and the Cardiovascular Epidemiology Unit in 2018 for a PhD in Health Data Science supervised by Prof. Michael Inouye and supported by the MRC-DTP. My PhD, completed in 2022, looked at machine learning tools used to predict protein-protein interactions and the carbon footprint of computational research.

As part of the SSI fellowship, I try to raise awareness around the environmental impacts of computational science and continue to help scientists across all fields to quantify and reduce the carbon footprint of their work.

Previous events

Title Start date End date
Collaborations Workshop 2024 Tuesday, 30 April 2024 Thursday, 02 May 2024
Environmentally Sustainable AI track at the Applied Machine Learning Days 2024 Saturday, 23 March 2024 Tuesday, 26 March 2024
Environmental Impacts of Computing in Health & Life Sciences Research Tuesday, 07 November 2023 Tuesday, 07 November 2023
Collaborations Workshop 2023 Tuesday, 02 May 2023 Thursday, 04 May 2023

Blog Posts

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