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    Xin Deng

    Senior Machine Learning Scientist at Microsoft

    Xin Deng is a highly skilled individual with expertise in various programming languages including Python, R, C, C++, Perl, Shell, Java, SQL, and SAS. His knowledge spans machine learning and data mining technologies such as Hidden Markov Model, neural networks, support vector machines, linear regression, random forest, boosting tree, deep learning technologies like CNN, RNN, and clustering methods, text mining, pattern recognition, statistical analysis, and algorithm design. He specializes in applications in Business, Healthcare, NLP, Recommendation Systems, Computer Vision, and Speech Recognition.

    Xin Deng completed a Doctor of Computer Science program at the University of Missouri-Columbia, as well as a Bachelor of Computer Science at Wuhan University.

    Xin Deng's illustrious career includes serving as a Senior Machine Learning Scientist at Microsoft. Additionally, he held multiple roles as a Workshop Chair at various IEEE Big Data Workshops focusing on technology for Bioinformatics and Health Informatics, Big Data Technology and Ethics Considerations in Customer Behavior and Customer Feedback Mining, and Textual Customer Feedback Mining and Transfer Learning. He has also worked as a Research Scientist at LexisNexis Inc, a division of Reed Elsevier.

    Xin Deng also served as the Chair of the Young Professional Group of the IEEE Orlando Section and was part of the team for the Mizzou-Apple Inc iPhone Software Design & Development Competition at the University of Missouri. His research experience includes positions as a Research Assistant at both the University of Missouri and Wuhan University.

    Xin Deng
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    Location

    Redmond, Washington, United States