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electric machines•Nanomaterials for next-generation electronic and photonic nanodevices•Oxide materials for MEMS piezoelectric and multiferroic sensors/actuators•Solid-state devices such as solar cells
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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interest includes field hydrology, sensor technologies and platforms for water resources monitoring, multilevel water observation and edge computing, artificial intelligence for hydrologic observation and
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, and adjusts controllers, sensors, and other operational attributes of electrical systems. Analyzes and documents the design, application, and condition of existing electrical systems and electrical
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, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models, with objectives to amplify
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foundational course is designed for first-year students across all engineering disciplines and focuses on cultivating problem-solving abilities, algorithmic thinking, and technical communication skills in a
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science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood biomarkers, and