Simone Riva
Senior Computational and Machine Learning Scientist in Genomics
With foundational knowledge and training rooted in computer science, I have seamlessly amalgamated myself within the domains of biology and genomics. My primary area of expertise revolves around designing, developing, and implementing cutting-edge and high-throughput bioinformatic tools that harness the potential of computational intelligence. I am particularly oriented towards the latest advancements in machine learning technologies.
Furthermore, I develop pipelines for projects that guarantee both efficiency and reproducibility, encompassing adept data management and the generation of data tailored for utilization in machine learning applications.
My main project revolves around deciphering non-coding regions of the genome, encompassing coding, splicing, regulatory elements, and structural aspects.
Recent publications
Zone Equalisation Normalisation for Improved Alignment of Epigenetic Signal.
Journal article
Wilson T. et al, (2026), Bioinformatics
Deciphering cis-regulatory elements using REgulamentary.
Journal article
Riva SG. et al, (2026), Bioinform Adv, 6
CREP: Cis-Regulatory Element Predictor Based on Fine-Tuned Enformer
Preprint
Stranieri N. et al, (2026)
Expert-Guided Supervised Annotation of Erythroid Differentiation in Single-Cell RNA-seq
Preprint
Enderti A. et al, (2026)