Speaker
Description
In an era where artificial intelligence has become a collaborator in scientific discovery, we present AION — the Artificial Intelligence Oracle of Neutrinos — a hybrid deep learning system designed to unravel hidden patterns in neutrino oscillation data across multiple experiments. Trained on real-world and simulated datasets from detectors such as Super-Kamiokande, DUNE, and JUNO, AION integrates methodologies from natural language processing, time-series prediction, and anomaly detection.
Through its quantum-enhanced architecture, AION identifies deviations from expected oscillation behaviors, potentially pointing toward unknown interactions beyond the Standard Model. This poster showcases AION’s ability to synthesize high-dimensional data from diverse sources — including cosmic, genomic, and particle domains — and generate actionable hypotheses. In an interactive twist, the audience is challenged to decode a mysterious anomaly flagged by AION, accessible via a QR-linked AI decryption challenge.
