Improved warning and control of the tokamak density limit via machine learning of an analytic stability boundary
Theory and Simulation of Disruptions Workshop, Princeton, New Jersey
Talks
Talks and presentations
Conference talks, seminars, and posters, most recent in each category first.
Invited
Correlation of the L-mode density limit with edge collisionality
66th Annual Meeting of the APS Division of Plasma Physics, Atlanta, Georgia
Contributed
Collisionality scaling of the tokamak density limit: data-driven analysis, cross-device prediction, and real-time avoidanceITER Session
67th Annual Meeting of the APS Division of Plasma Physics, Long Beach, California
Correlation of the L-mode density limit with edge collisionality
IAEA 3rd Technical Meeting on Plasma Disruptions and their Mitigation, ITER Headquarters, France
Position: Opportunities Exist for Machine Learning in Magnetic Fusion EnergyICML Oral
41st International Conference on Machine Learning (Oral), Vienna, Austria
Correlation of the L-mode density limit with edge collisionality
44th ITPA MHD, Disruptions & Control Topical Group Meeting, Remote
Density limit prediction at DIII-D & beyond: an offline analysis
27th Workshop on MHD Stability Control, Boulder, Colorado
Investigating the robustness of machine learning-based disruption prediction with synthetic training data
26th Workshop on MHD Stability Control, Spokane, Washington
Predicting neutron yield of NIF ICF experiments by applying machine learning to a small (n<150) and heterogeneous experimental dataset
62nd Annual Meeting of the APS Division of Plasma Physics, Remote
Finding correlations in inertial confinement fusion experimental data using machine learning
61st Annual Meeting of the APS Division of Plasma Physics, Fort Lauderdale, Florida
Seminars and outreach
Distilling the density limit in tokamaks using data-driven techniques
AstroAI Journal Club - Harvard & Smithsonian Center for Astrophyics, Cambridge, MA
The impact of disruptions on the economics of a tokamak power plant
MIT Energy Intiative - Fusion Study Team, Cambridge, MA
What Jurassic Park gets wrong about Chaos Theory
TEDx Asbury Park, Asbury Park, New Jersey
Posters
Prediction and control of the tokamak density limit via edge collisionalityOutstanding poster
13th ITER International School, Nagoya, Japan
Data-driven tokamak density limit boundary identification
65th Annual Meeting of the APS Division of Plasma Physics, Denver, Colorado
Investigating the robustness of machine learning-based disruption prediction with synthetic training data
64th Annual Meeting of the APS Division of Plasma Physics, Spokane, Washington
Identifying physical disruption boundaries in Alcator C-Mod using linear Support Vector Machines
63rd Annual Meeting of the APS Division of Plasma Physics, Pittsburgh, Pennsylvania