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Reinforcement Learning with Quantum Algorithms: Simulating Nematode Behaviour

Sunday 2:50 PM–3:20 PM in Ballroom 1

What happens when you combine quantum computing, neuroscience, and reinforcement learning—all in Python? This talk explores how parameterized quantum circuits can be used as “brains” for agents inspired by the nematode C. elegans, and how these agents learn to navigate their world using reinforcement learning. We’ll see how quantum and classical approaches compare, and what this means for the future of AI and quantum machine learning.

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Can quantum computing help us build smarter, more efficient learning agents? In this talk, we’ll dive into a Python project that simulates the behaviour of the nematode C. elegans using reinforcement learning—once with a classical neural network, and once with a quantum circuit as the agent’s brain.

We’ll cover:

Whether you’re a quantum enthusiast, ML practitioner, or just curious about the intersection of biology and AI, you’ll leave with new ideas and practical tools for exploring these fields in Python.

Chris Zaharia

Chris is a software engineer passionate about the intersection of neuroscience, machine learning, and quantum computing.

He’s currently a Staff Software Engineer at Q-CTRL, building applications to tune and optimize quantum computers. Previously, he was the CTO and co-founder of startups in online education and brain-computer interfaces.

Outside of work, Chris enjoys exploring new technologies, hiking along Australia's coasts and bushland, and playing video games.