Lorenzo Farina

Lorenzo Farina is a Full Professor at Sapienza University of Rome's Faculty of Information Engineering, Computer Science and Statistics, specializing in Electronic and Computer Bioengineering (ING-INF/06). With over 25 years of academic leadership, he co-founded Italy's first Bioinformatics degree program and established key oncology precision medicine initiatives, maintaining active collaborations with Harvard Medical School's network medicine division.

His educational background includes a cum laude Electronic Engineering degree and PhD in Systems Engineering, both from Sapienza University. These foundational studies evolved into pioneering work in positive linear systems theory, evidenced by his highly-cited Wiley textbook Positive Linear Systems: Theory and Applications (2000).

Farina's research centers on network medicine – applying complex network science to molecular medicine since his 2004 breakthrough. His work spans cancer mechanisms (breast, glioblastoma, lung), drug repositioning (including COVID-19 applications), and liquid biopsy biomarker development. Current projects focus on miRNA-based network biomarkers for cancer diagnostics and immunotherapy response prediction, integrating multi-omics data through advanced computational frameworks.

Analysis of his 15 most recent publications (2024-2025) reveals dominant themes: sexual dimorphism in cancer networks (MIRROR platform), immunotherapy response signatures, and critical examinations of AI's role in precision medicine. His work consistently bridges computational innovation with clinical applications, particularly in oncology diagnostics and therapeutic optimization.

His scientific recognition includes:

• 2001 Guillemin-Cauer Award for best IEEE Transactions on Circuits and Systems article
• 2014 SysBio Award for annual best publication

Farina actively mentors through interdisciplinary programs he established, including the Network Oncology doctoral program. His laboratory collaborations span Sapienza's Oncogenomics and Immunology Laboratories, Harvard's Channing Division of Network Medicine, and clinical departments in oncology and radiology, driving translational research from computational models to patient applications.

He leads multiple research teams focused on network-based diagnostics, including the MIRROR platform for cancer disparity analysis and liquid biopsy development teams investigating circulating miRNA networks for early cancer detection across multiple malignancies.