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Naoki Abe

Developer Advocate

Artificial intelligenceData sciencePythonJavaMachine learning

Naoki Abe is a distinguished research staff member and manager of Foundations of Computational and Statistical Learning group within the Foundations of Trusted AI Department, IBM Research AI. Dr. Abe obtained his B.S. and M.S. degrees in computer science from MIT in 1984, and Ph. D. in computer science from University of Pennsylvania in 1989. He has been with IBM Research since 2001, conducting research in the development of novel machine learning methodologies that open up new applications in a variety of areas of business analytics. His research activities have ranged from applications of reinforcement learning to business analytics, methods for anomaly detection, temporal causal modeling, cost-sensitive learning and on-line active learning, among other topics. Methodologies that he co-developed through these research efforts have made their ways into a number of IBM offerings, including Temporal Causal Modeling engine in SPSS Modeler and Statistics, Granger anomaly detection engine in Smart Cloud Predictive Insights, the Tax Collections Optimizer and Signature Solutions “Next Best Action” and “CFO-dashboard.”

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