The project
ALA — Advanced Laboratory Automation — launches as a joint research and development project between Gruppo INPECO, a world leader in laboratory automation, and the BioRobotics Institute at the Scuola Superiore Sant’Anna in Pisa. The total investment is 3.5 million euros, with a team of 30 researchers involved.
Stefano Noferi serves as AI and Cloud Software Architect, responsible for designing the software architectures and artificial intelligence modules.
Research directions
The project is structured around three main research directions:
- Deep Learning for skin lesion detection: convolutional neural networks (CNN) and image segmentation techniques for the automatic classification of dermatological images, with benchmarks that surpass human performance.
- Integrated multimodal sensing: fusion of data from heterogeneous sensors with Deep Learning-based inference for real-time analysis.
- Complete biological sample traceability: an end-to-end system for monitoring and certifying the entire lifecycle of laboratory samples.
Technology stack
The architecture is built on Python, Django, TensorFlow for the backend and AI models, React and React Native for the interfaces, Azure for the cloud, Docker for containerization, Redis and PostgreSQL for caching and data persistence.
Clinical validation
The models are validated in collaboration with the dermatology centers of Siena and Livorno, ensuring the transition from research to real clinical practice.