Giovanni Dall'olio is a Head of Data Science and Machine Learning with 17 years' experience applying bioinformatics, genomics and ML to drug discovery and diagnostics across pharma, startups and consulting. He combines hands-on expertise in omics pipelines, variant calling and large-scale data engineering (Databricks, Delta Lake) with leadership in building ML-backed products and coaching cross-functional teams. Notable achievements include migrating omics workflows to Delta Lake with a 90% cost reduction, developing end-to-end infrastructure for precision-medicine platforms, and contributing backend improvements to the widely used clusterProfiler enrichment tool. Comfortable bridging research and product, he applies deep-learning methods (VAE, PyTorch Lightning) and LLM agents for data curation while helping early-stage ventures define market and data-governance strategy. Based in North Hertfordshire, he actively consults and mentors, blending academic rigor from a PhD in human population genetics with pragmatic product delivery.
17 years of coding experience
5 years of employment as a software developer
Bioinformatics bioinformatics science biology computer science, Bioinformatics bioinformatics science biology computer science at Alma Mater Studiorum – Università di Bologna
PhD in BioMedicine Human Population Genetics, PhD in BioMedicine Human Population Genetics at Universitat Pompeu Fabra
:bar_chart: A universal enrichment tool for interpreting omics data
Role in this project:
Back-end Developer
Contributions:14 commits, 9 PRs, 2 comments in 8 days
Contributions summary:Giovanni primarily focused on enhancing the functionality of the `clusterprofiler` package by implementing a formula interface for the `compareCluster` function. They refactored code, fixed bugs, and added support for multiple grouping variables. They also addressed a bug related to the order of factors and made improvements to the plotting functionality, showing an understanding of the package's core logic.
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Giovanni Dall'olio - Head Of Data Science And Machine Learning