I am a Senior Bioinformatics Scientist with a Ph.D. in Bioinformatics and over six years of experience in computational biology, oncology, and real-world evidence analysis. My career has been driven by the passion to transform complex biological data into clear insights that advance science and improve patient care. From early on, I have been fascinated by the challenge of bridging data science with life sciences, and this motivation continues to inspire my work today.
My professional journey
2017 – 2020
2020 – 2024
2025 – Today
Began in 2017 at the University Hospital Policlinico in Catania, where I developed an eHealth platform to remotely monitor patients with rare lung diseases, integrating real-world clinical data to support better disease management. During a visiting research position at the Institute of Oncology Research in Bellinzona, I expanded my expertise in transcriptomics and pharmacological response, focusing on gene expression in ultraconserved regions.
From 2020 to 2024, I worked at the Mediterranean Institute of Oncology in Italy, where I contributed to cancer research through the integration of multi-omics and clinical data. I designed pipelines for NGS interpretation, explored liquid biopsy applications, and applied machine learning models for biomarker discovery, patient stratification, and prognostic modeling work that resulted in several peer-reviewed publications.
Since 2025, I have been a Senior Bioinformatics Scientist at Prepaire Labs in Dubai, leading the development of digital twin models that integrate omics, patient-reported outcomes, EHRs, and clinical trial data. These models enhance precision medicine by providing personalized recommendations and strengthening the predictive power of translational oncology.
Expertise
My expertise spans multi-omics data integration (genomics, transcriptomics, proteomics, microbiome), real-world evidence analytics, predictive modeling and AI, and the design of robust Nextflow pipelines for high-throughput data. I thrive in cross-functional collaborations, working alongside clinicians, pathologists, and data scientists to ensure that computational insights are clinically relevant.
Technically, I am proficient in R and Python for data analysis, statistical modeling, and machine learning; I leverage cloud platforms such as AWS to scale computational workflows; and I use Git version control to ensure reproducibility and collaborative development.
Looking ahead, my vision is to continue advancing the field of oncology and precision medicine by integrating real-world data and computational modeling. I am committed to pushing the boundaries of bioinformatics to accelerate medical discoveries and ultimately improve patient outcomes.