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Overview

Welcome to the Scalable Analytics Research Group (Scalatics) at the Center for Computational Learning Systems, Columbia University, New York. The group is led by Haimonti Dutta.

Our research involves analysis of very large data sets (typically peta-or tera-byte scale) using sophisticated machine learning and data mining algorithms. Often the data is stored in distributed (such as cloud computing infrastructure) or ubiquitous computing environments (such as mobile ad-hoc networks, peer-to-peer computing infrastructures and sensor networks). Learning involves solving large scale optimization problems, designing distributed and parallel learning algorithms, probabilistic inference, data mining and machine learning. We devise new machine learning algorithms, perform exploratory data analysis, build models and systems that can scale to large datasets. Application domains involve digital humanities, computational sustainability and health care. More information is available here.