TRIPODS: From Foundations to Practice of Data Science and Back

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In recent decades, scientific and technological fields have experienced "data moments" as researchers recognized the potential of drawing new types of inferences by applying techniques from computational statistics and machine learning to ever-growing datasets. At the same time, everyday life is increasingly saturated with products of data analysis: search engines, recommendation systems, autonomous vehicles, etc. These developments raise fundamental methodological questions, including how to collect and pre- pare data for analysis, and how to transform statistical inferences into effective action and new statistical inquiries. To address these questions, it is necessary to develop theoretical foundations for the practice of data science, and to provide practitioners with sound and practically relevant methodological training. The Columbia TRIPODS Institute pursues these goals through an integrated program of research in data science foundations, curriculum development, and center-building activities. The research program seeks to provide theoretical understanding of practical heuristics, develop modular and well-structured toolkits of computational primitives for data science, and to support the entirety of the data science cycle, from data collection and annotation, to the assessment of the analysis product. The Institute pursues programs of research, education and center-building aimed at articulating theoretical foundations for data science. Its activities aim to have a major impact in shaping this emerging field. The research directions include understanding tractable classes of optimization problems, developing primitives that support efficient computation on data, and developing methodological foundations for interactive protocols in data science. These directions address challenging problems at the interface between theory and practice, the solutions of which require ideas spanning mathematics, statistics, and computing. The educational activities articulate model curricula in data science at the MS/professional and PhD levels, including interdisciplinary courses aimed at building a common language for a new generation of scientists and engineers. Center building activities are organized around cross-disciplinary themes and structured to encourage interaction across disciplines and to develop a common methodological community in Foundations of Data Science. These research and educational activities-including workshops, summer schools, distinguished lecture series, long-term visits, and outreach- help to further define and disseminate a common language for foundational research and education, and to increase diverse participation in data science. Located within the Center for Foundations of Data Science in the Data Science Institute at Columbia University, the Institute is at the center of the Northeast Big Data Hub. This position supports expansion of activities within Columbia, and also with other Big Data Hub members, TRIPODS Institutes, and research/industry organizations. Funds for the project come from CISE Computing and Communications Foundations, CISE Information Technology Research, MPS Division of Mathematical Sciences, and MPS Office of Multidisciplinary Activities.