Two lines, six sub-areas.
Every project is the same act on a different substrate: recovering a mechanism from the traces it leaves. Line A pursues it through retrieval and language models; Line B through differential equations with neural components.
Line A — frontier
TRAG — Targeted Retrieval-Augmented Generation
Hybrid syntactic-vector retrieval and LLM generation over a dataset of several thousand EU regulatory documents. In evolution as a mature prototype. The instrument from which both applied projects derive.
Neuro-symbolic model identification for ecosystem studies and management
Long-term Lake Maggiore zooplankton observations are used to derive and evaluate models.
RAG-driven calibration of ecosystem simulation models
Documents and data from Lake Varese will be collected to calibrate a number of lake simulation models.
Line B — consolidated
Inverse problems for ecosystem studies
Population dynamics as a tool for understanding the role of zooplankton in the stability of aquatic ecosystems.
Material accountancy & pattern recognition
State-space neural networks and normalising flows for loss-pattern detection in near-real-time nuclear material accountancy.
Inverse physiology & radioecology
Anatomical graph neural networks over compartmental kinetics, reopening the Zn-65 physiology of Lepomis gibbosus.