85 citations · 286 across the 20 of their papers we have counts for
22 papers
MGKDB: An IMAS-aligned multicode gyrokinetic simulation database for reproducible fusion turbulence modeling and data-driven analysis
Craig Michoski, David R. Hatch, Dongyang Kuang +14
Expensive fusion simulations are commonly preserved in code-specific formats that limit discovery, comparison, and reuse. We present the Multiscale GyroKinetic DataBase (MGKDB), an…
The Fusion Equilibrium Challenge: Inferring Magnetic Geometry Without Magnetic Diagnostics
Tapan Ganatma Nakkina, Matthew Waller, Craig Michoski +6
Next-generation fusion reactor devices such as SPARC, ARC, and CFETR will operate in extreme neutron environments that compromise the magnetic sensors traditionally used to reconst…
The Data Fusion Labeler (dFL): Challenges and Solutions to Data Harmonization, Labeling, and Provenance in Fusion Energy
Craig Michoski, Matthew Waller, Brian Sammuli +14
Fusion energy research increasingly depends on the ability to integrate heterogeneous, multimodal datasets from high-resolution diagnostics, control systems, and multiscale simulat…
Commuting Distance Regularization for Timescale-Dependent Label Inconsistency in EEG Emotion Recognition
Xiaocong Zeng, Craig Michoski, Yan Pang +1
In this work, we address the often-overlooked issue of Timescale Dependent Label Inconsistency (TsDLI) in training neural network models for EEG-based human emotion recognition. To…
Quantifying Resolution Limits in Pedestal Profile Measurements with Gaussian Process Regression
Norman M. Cao, David R. Hatch, Craig Michoski +4
Edge transport barriers (ETBs) in magnetically confined fusion plasmas, commonly known as pedestals, play a crucial role in achieving high confinement plasmas. However, their defin…
Emotion Classification from Multi-Channel EEG Signals Using HiSTN: A Hierarchical Graph-based Spatial-Temporal Approach
Dongyang Kuang, Xinyue Song, Craig Michoski
This study introduces a parameter-efficient Hierarchical Spatial Temporal Network (HiSTN) specifically designed for the task of emotion classification using multi-channel electroen…