Workshop on the Algorithmic, Mathematical, and Statistical Foundations of Data Science

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A workshop on the Algorithmic, Mathematical, and Statistical Foundations of Data Science will be held April 28-30, 2016 in Arlington, VA. The event will bring together leading researchers in computer science, mathematics, and statistics to address foundational issues related to data science. The objectives of the workshop are three-fold: (i) identify fundamental areas in the emerging discipline of Data Science where collaboration between computer scientists, mathematicians, and statisticians is necessary to achieve significant progress; (ii) Assess how collaboration between computer scientists, mathematicians, and statisticians could potentially contribute to workforce development by advancing and transforming the Data Science research training of Ph.D. students and post-docs; and (iii) Suggest different infrastructure modalities that could significantly promote and advance such collaborations. The main deliverable of the workshop is a white paper that will serve as a guideline for professional societies and funding agencies. The rapid emergence of the Big Data phenomenon presents both opportunities and challenges. While massive data may allow the generation of models and the design of algorithms that have improved inferential power, such models and algorithms may be less successful on modest-sized data sets. The challenge for researchers is to develop theoretical principles that will allow the scaling of inference and learning to massive-scale datasets, and algorithms that control errors even in the presence of heterogeneity in the data generation and data sampling processes. These challenges will require collaborations between researchers representing theoretical computer science, mathematics, statistics, machine learning and data mining, and high performance computing. This award supports a workshop that brings together leaders from these communities of researchers to discuss the challenges and opportunities for collaborative work in this developing field.