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职业迁徙
个人简介
I joined IBM Watson in 2014, and have since been working on semantic analysis in natural language understanding, with applications in conversational systems, question answering, knowledge discovery, among others. In 2020 I joined Watson Health to work on semantic analysis in healthcare solutions.
Over my career I have developed many methods in artificial intelligence. I seek to discover and represent knowledge embedded in large, high-dimensional data sets by algorithmic processes. More specifically, I design methods for natural partitioning of data, systematic search for correlations, characterizing complexity of dependences, generation and evaluation of feature transformations, dynamic adaptation of established models, and above all, classification. On classification, I pioneered methods for multiple classifier systems (a.k.a. ensemble learning), random decision forests, and later, data complexity analysis. On a broader theme, I explored methods and tools for interactive data visualization and analysis, and computational modeling and simulation of complex systems.
Over my career I have developed many methods in artificial intelligence. I seek to discover and represent knowledge embedded in large, high-dimensional data sets by algorithmic processes. More specifically, I design methods for natural partitioning of data, systematic search for correlations, characterizing complexity of dependences, generation and evaluation of feature transformations, dynamic adaptation of established models, and above all, classification. On classification, I pioneered methods for multiple classifier systems (a.k.a. ensemble learning), random decision forests, and later, data complexity analysis. On a broader theme, I explored methods and tools for interactive data visualization and analysis, and computational modeling and simulation of complex systems.
研究兴趣
论文共 155 篇作者统计合作学者相似作者
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arXiv (Cornell University) (2018): 9528-9533
IEEE Transactions on Smart Gridno. 2 (2017): 738-748
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