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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
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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
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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
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optimal spatial arrangement (single/multiple lines, angle of incidence) of PBs for a given coastline morphology and flood hazard profile to minimise inland inundation, assessed using coupled CFD and
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, productivity, energy efficiency, and resilience in building construction. Potential research interests include, but are not limited to: 1. Develop optimization processes for industrialized mass customization
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through the integration of high-performance materials, robotics, automation, computation, and process optimization. Affordable mass customization of building designs that are produced with advanced
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local and state building codes throughout the U.S. with the end goal of optimizing onsite and offsite construction and industrialized mass customization. 2. In collaboration with interdisciplinary