Staff

Ivan Merelli

Primo Ricercatore
E-Mail

ivan.merelli@cnr.it

PHONE

+390226422602

LOCATION

Segrate

ROOM (floor/number)

6/02

I am a Senior Staff Scientist at the Institute for Biomedical Technologies of the National Research Council (ITB-CNR), where I conduct research at the intersection of computational biology, high-performance computing, and artificial intelligence. My work focuses on the design of scalable analytical pipelines for single-cell and spatial omics, multi-omics integration, and immune-repertoire profiling. I develop HPC-oriented workflows that combine statistical modelling, machine learning, and modern AI approaches to extract robust biological insights from large and heterogeneous datasets. I collaborate closely with clinical and experimental partners, including research groups at IRCCS San Raffaele and the Fondazione Telethon, contributing computational leadership to projects in cancer biology, immunology, and gene therapy. A key part of my activity involves building automated, reproducible, and AI-augmented pipelines for cell-type annotation, variant interpretation, multi-omics harmonization, and structure-based modelling of biomolecules. In addition to algorithmic development, I design web-based tools and interactive platforms that make advanced analyses accessible to multidisciplinary teams, ensuring usability, reproducibility, and efficient integration with institutional HPC infrastructures. I also support the planning and optimization of computational environments, including GPU-accelerated workflows and cloud-enabled solutions. My overarching goal is to bridge cutting-edge computational methods with real biological and clinical questions, enabling data-driven discoveries and advancing the technological capabilities of the CNR research ecosystem through strong collaborations and innovative computational solutions.

Multiomic integration to identify regulatory pathways, gene modules, protein networks, and composite signals associated with pathological phenotypes.

Investigation, High Throughput Virtual Screening (HTVS), rational and de novo design, drug repurposing, and iterative optimization of pharmacologically active molecules and other therapeutic entities (like small molecules and RNAs) aimed at treating or preventing pathological conditions in living organisms.

Semantic data modeling for advanced reasoning, decision support, and knowledge discovery by linking heterogeneous datasets through semantic relationships.

Development and maintenance of HPC clusters (HPC Infrastructure Management) ensuring predictable and scalable execution of intensive calculations.

Deployment and management of Computational Infrastructure (Cloud and HPC) for Life-Science data analysis, storage and sharing