Daniel Kaslovsky

Ph.D., Applied Mathematics

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Daniel Kaslovsky


I received my Ph.D. in applied mathematics from the University of Colorado at Boulder and was awarded a NSF Postdoctoral Fellowship for research at the National Institute of Standards and Technology (NIST). I now develop machine learning algorithms for information/cyber security applications at a technology company in Boulder, Colorado.

My research has focused on developing new mathematical analyses and algorithms for finding structure in noisy, high-dimensional data. I am particularly interested in statistical, geometric, and machine learning approaches for analyzing large data sets, efficient sensing and computation using randomized algorithms, and modern signal/image processing.

Information for the reading course I developed is available here: "Recent Topics in Big Data".