Héctor Climente-González
Lead Scientist at Novo Nordisk. London, United Kingdom.
As a Lead Data Scientist at Novo Nordisk, I design and deploy AI/ML methodologies for early target discovery and precision medicine — with a strong focus on genetics.
I have 13+ years of experience in computational biology and applied statistics. I completed my PhD at CBIO, a leading bioML laboratory, under the supervision of Chloé-Agathe Azencott, where I explored graph-based methods for genetic studies. I then conducted my postdoctoral research at RIKEN AIP with Makoto Yamada, developing novel AI/ML methods for feature selection.
My research focuses on multi-omics integration, explainable ML and systems biology. I’m an advocate for reproducible research and an advanced Nextflow developer. I’m detail-oriented, proactive, and wired to fix what’s broken — ideally before anyone notices.
news
| Nov 15, 2024 | I was promoted to Lead Data Scientist. I will be working on AI/ML for target and biomarker discovery. |
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| Mar 07, 2024 | Our model for cardiovascular disease risk prediction got highlighted in Novo Nordisk’s Capital Markets Day. |
| Jan 13, 2024 | Our preprint on predicting cardiovascular disease risk using interpretable ML is out! This work was conducted in partnership with Microsoft Research. |
latest posts
| Apr 01, 2025 | SHAP values |
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| Feb 18, 2025 | Knockoffs |
| Jan 27, 2025 | Random walks and Markov chains |
selected publications
- Interpretable Machine Learning Leverages Proteomics to Improve Cardiovascular Disease Risk Prediction and Biomarker IdentificationmedRxiv, 2024
- A network-guided protocol to discover susceptibility genes in genome-wide association studies using stability selectionSTAR protocols, 2023
- Interpretable network-guided epistasis detectionGigaScience, 2022
- Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional dataBioinformatics, 2019
- The functional impact of alternative splicing in cancerCell reports, 2017