13th November 2026, 16:30 – 17:30 CET

Politecnico di Milano – Fassò room  and on-line at  webex-room

 Quantum Machine Learning (QML) stands as an innovative field at the intersection of Quantum Computing (QC) and Artificial Intelligence (AI). This presentation explores the transition from classical machine learning to quantum-driven spatial systems within the current Noisy Intermediate-Scale Quantum (NISQ) era. We will examine how Variational Quantum Algorithms (VQAs) and Quantum Kernel methods can address high-dimensional environmental data for NISQ devices (e.g., IBM quantum systems) and explore their associated challenges. 

Speaker: Thilanka Munasinghe, PhD