Sort by
Refine Your Search
-
Country
-
Employer
-
Field
-
‑space exploration, and on‑line operational optimization of power systems. Your tasks in detail: Become familiar with our previously developed neural network superstructure for learning iterative
-
efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation of models on patient-specific geometries obtained from MRI data Participation in conferences
-
to accelerate solving AC power flow (AC-PF) computations, potentially facilitating real‑time contingency analysis, rapid design‑space exploration, and on‑line operational optimization of power systems
-
prediction Integration of domain decomposition methods into the learning framework to enable efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation
-
experiments, behavioral research, econometric and causal inference approaches, optimization and analytical modeling, and data-driven techniques such as machine learning and large language models. Our work is