Shenson Joseph

The quantum internet is an emerging network that distributes quantum entanglement rather than classical bits, enabling capabilities no classical infrastructure can replicate: provably secure communication through quantum key distribution (QKD), blind and distributed quantum computing, networked quantum sensing, and a future backbone linking quantum processors across cities and continents.

Yet the path from laboratory demonstrations to a usable network is obstructed by hard physics. Managing such a network—deciding when to generate, store, swap, or purify entanglement, and how to route it end-to-end before it expires—is a high-dimensional, stochastic, latency-critical control problem that overwhelms hand-tuned heuristics. This talk presents the case that artificial intelligence is the natural control plane for the quantum internet.

Over a full hour, we build from quantum-networking first principles to the open research frontier: how reinforcement learning, graph neural networks, and predictive sequence models can govern entanglement routing, repeater and quantum-memory scheduling, real-time QKD adaptation, and dynamic topologies such as LEO satellite constellations—closing with the open problems that will define the field over the coming decade.

Biography:

Lead AI/ML Engineer (VP) | PhD Candidate, AI & Quantum Computing
IEEE Senior Member | BCS Fellow | Research: AI-Optimized QKD for LEO Satellite Networks