Dong Meng is a data scientist at MapR, where he helps customers solve their business problems with big data by translating the value from customers’ data and turns it into actionable insights or machine learning products. His recent work includes integrating open source machine learning frameworks like PredictionIO and XGBoost with MapR’s platform. He also created time series QSS and deep learning QSS as a MapR service offering. Dong has several years of experience in statistical machine learning, data mining, and big data product development. Previously, he was a senior data scientist with ADP, where he built machine learning pipelines and data products for HR using payroll data to power ADP Analytics, and a staff software engineer with IBM, SPSS, where he was part of the team that built Watson analytics. During his graduate study at the Ohio State University, Dong served as research assistant, where he concentrated on compressive sensing and solving point estimation problems from a Bayesian perspective.
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