Mauro Nievas Offidani
MD · PhD
AI & Data Science for Healthcare
Applying artificial intelligence and data science to transform information into knowledge and improve medical research and healthcare.
AI & Data Science for Healthcare
Applying artificial intelligence and data science to transform information into knowledge and improve medical research and healthcare.
Hi! I'm Mauro, a Medical Doctor and Senior Data Scientist working at the intersection of healthcare and AI. I combine deep medical domain knowledge with hands-on AI and data science development — from research to production.
My background is academic-solid and industry-tested: I hold a PhD in Medical Imaging and an MSc in Epidemiology & Health Policy, and I've spent 7+ years delivering end-to-end projects across NLP, computer vision, RAG pipelines, and clinical automations — as individual contributor, team lead, and consultant.
I'm drawn to complex, high-stakes problems where medical expertise and technical depth both matter.
A curated set of technologies I use to build
AI-powered healthcare solutions and data-driven applications.
Python
FastAPI
Google Cloud
GitHub
LangChain
LangGraph
Neo4j
N8N
Vertex AI
BigQuery
Power BI
HuggingFace
FHIR
HL7
SNOMED CT
DICOM
End-to-End AI Projects
From scoping to deployment: RAG pipelines, NLP systems, medical imaging models and more, built for real clinical environments.
AI Strategy & Consulting
Helping healthcare organizations identify where AI creates value and how to implement it responsibly.
Clinical Automations
Streamlining repetitive clinical and administrative workflows using AI agents and automation tools.
Medical Database Design & Interoperability
Designing structured clinical databases and enabling data exchange using FHIR, HL7, and SNOMED CT standards.
Research & Development
Collaborating on applied research projects at the intersection of medicine, data science, and AI.
Clinical Data Analysis & Visualization
Turning complex clinical datasets into clear, actionable insights through rigorous analysis and visual storytelling.
MultiCaRe Dataset
An open-source multimodal dataset of 100K+ clinical cases and 140K+ medical images, built from PubMed Central case reports to advance clinical AI research.
Multiplex Classification Framework
A theoretical framework for complex ML classification supporting any number of classes and logical relations between them, with application to medical image classification.
LLM Fine-tuning for Clinical Trial Matching
Fine-tuned open-source LLMs for patient-to-clinical trial matching, achieving performance parity with proprietary models like GPT-4 at a fraction of the cost.
Oncology NLP Models
Built and presented state-of-the-art NLP models for oncology clinical text at the NLP Summit, using Spark NLP for named entity recognition across cancer-related entities.
Have a project in mind, need advice, or just want to connect? Pick whatever works best for you.
