Aza Jalalvand

Research scholar at Princeton University. Uses deep reinforcement learning to control plasma instabilities in nuclear fusion reactors.

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Apr 29, 2024 • 42min

Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand - #682

Aza Jalalvand, a research scholar at Princeton University, dives into the fascinating realm of using deep reinforcement learning to stabilize plasma in nuclear fusion reactors. He discusses the development of a model to combat the tearing mode instability while collecting complex data from fusion experiments. Aza highlights the critical role of machine learning in enhancing plasma understanding, the challenges of real-time data management, and the promising future of AI in clean energy production. Tune in for insights on the electrifying intersection of AI and fusion technology!