Quantum Information Technology Lab

Our research explores the frontiers of quantum computational capabilities and quantum artificial intelligence with the purpose of bridging the gap between theoretical potential and practical realization. We move beyond abstract models to develop the tools necessary to make scalable quantum computing a reality.

We investigate practical tools for near-term and future quantum devices. We use ML and Reinforcement Learning to automate circuit synthesis and tailor quantum compilation to specific hardware, ranging from Superconducting qubits to Neutral Atom architectures. We focus on building efficient Quantum Machine Learning frameworks by optimizing hardware performance through classical methods, making quantum systems more practical and computationally effective.