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A Collaborative and Interactive Space for Data Science

Tim Kraska

Panelist Spotlight

Tim Kraska is an Associate Professor of Electrical Engineering and Computer Science in MIT’s Computer Science and Artificial Intelligence Laboratory, co-director of the Data System and AI Lab at MIT ([email protected]), and co-founder of Einblick Analytics. Currently, his research focuses on building systems for machine learning, and using machine learning for systems to build instance-optimized systems. Tim is most known for developing techniques to make Data Science more interactive and collaborative, and creating the first Learned Index structure and Learned Query Optimizer.

Event Description: Unleashing the full potential of data and AI requires a paradigm shift in the algorithms and tools used to analyze data and build models towards more interactive systems with highly collaborative and visual interfaces. Ideally, data scientists and domain experts should be able to closely work together and make discoveries together by directly manipulating, analyzing and visualizing data on the spot as a team, instead of having week-long forth-and-back interactions between them. Current visualization and workflow tools are ill-suited for this purpose. They were not designed to be interactive nor to support teams to actually work together rather than just share final results. Similarly, most machine learning algorithms are not able to provide initial answers at "human speed" (i.e., seconds), nor are existing methods sufficient to convey the impact of the various risk factors, such as multi-hypothesis problems. Finally, most visual data exploration tools still fail when used over large datasets or require horrendous loading times before any real-work can begin. Northstar (A Novel System) is designed by famous scholars in the field to address all these problems. Let us hear how they are solving these problems

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NYC Data Science Academy

NYC Data Science Academy’s mission is to provide accelerated data science training programs that prepare people for employment as data science professionals and to offer continuing education courses for professional development.