Author: nc1514

Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand Watch PCG Research Scientist Aza Jalalvand talk about machine learning and fusion on the TWIML podcast

Dr. Daniel Dudt has successfully defended his thesis on “stellarator optimization” this 2024, marking a significant milestone in his academic journey. His rigorous research and innovative approach have culminated in his next role as a Senior Scientist at Thea Energy. Best wishes on your exciting journey ahead!

Dr. Rory Conlin defended his thesis on “Stellarator optimization” in 2024, demonstrating outstanding proficiency and dedication. His work, which has been a cornerstone of recent lab discussions, will continue as he transitions to a postdoctoral role at the University of Maryland. Your future in the field looks bright, and we look forward to seeing where…

Dr. Susan Redmond showcased her scholarly excellence in 2023 with her defense of “CORRECTION OF QUASI-STATIC WAVEFRONT ERROR DRIFTS IN WIDE-FIELD AND HIGH-CONTRAST IMAGING TELESCOPES”. Your next adventure as a Postdoc at Caltech promises to be just as groundbreaking. We’re all cheering for your continued success and discoveries!

Cutting-Edge Fusion Research by Princeton’s Plasma Control Group Read about our research, led by Egemen Kolemen and conducted by researchers including Jaemin Seo, SangKyeun Kim, and Azarakhsh Jalalvand, affiliated with Princeton University and Princeton Plasma Physics Lab (PPPL). Publication on NatureAvoiding fusion plasma tearing instability with deep reinforcement learning Researchers Involved: Jaemin Seo, SangKyeun Kim, Azarakhsh Jalalvand, Rory…