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个人简介
His research centers on “Engineering Statistics”, in particular, process and product quality control and optimization methods in industry, areas related to Time Series Analysis and Control, Design of Experiments, Response Surface Methodology, and Reliability Engineering. Due to the wide availability of sensors and the consequently increasing datasets, his work in control and optimization has evolved over the last decade to deal with problems involving not only larger but more complex datasets, such as large geometrical (or geometrical-spatial) datasets, specifically, functional, shape, surface and volumetric data (i.e., data that occurs in 1D or 2D-manifolds) as well as point cloud and image data, in work at the intersection of Statistical methodology, Engineering metrology and Machine Learning methods. His interests in on-line process optimization has resulted in recent work in the area of Active Learning with engineering applications. In addition to working in data-based engineering problems, Castillo has maintained secondary collaborations with scientists working in biology, evolutionary theory, and nutrition.
研究兴趣
论文共 180 篇作者统计合作学者相似作者
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INFORMS journal on data science (2023)
Journal of evolutionary biologyno. 9 (2023): 1266-1281
SSRN Electronic Journal (2022)
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