Scholar
Héctor Climente-González
Google Scholar ID: tK7i7zwAAAAJ
Novo Nordisk Research Centre Oxford
Citations & Impact
Citations
963
H-index
9
i10-index
8
Publications
18
Co-authors
5
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers including 'The functional impact of alternative splicing in cancer' in Cell Reports, 'Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data' in Bioinformatics, 'Interpretable network-guided epistasis detection' in GigaScience, and 'A network-guided protocol to discover susceptibility genes in genome-wide association studies using stability selection' in STAR Protocols.
Research Experience
- Lead Data Scientist at Novo Nordisk, working on AI/ML for target and biomarker discovery. Conducted doctoral and postdoctoral research at CBIO and RIKEN AIP respectively.
Education
- 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. Conducted postdoctoral research at RIKEN AIP with Makoto Yamada, developing novel AI/ML methods for feature selection.
Background
- 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. 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.
Miscellany
- Blogs about topics such as Independent Component Analysis, How do vector databases work, and Cross-entropy. Intuition and applications.
