The rapid democratization of data has placed its access and analysis in the hands of the entire population. While the tools for rapid and large-scale data processing have continued to reduce the time to compute analysis results, the techniques to help users better and more easily visualize their data, clean and prepare their data, and understand what their results mean are still lacking. In this talk, I will provide an overview of our lab's recent work on addressing each stage of data analysis — data cleaning, data visualization, and explanation.
Eugene Wu is broadly interested in technologies that help users play with their data. His goal is for users at all technical levels to effectively and quickly make sense of their information. His focus is in solutions that ultimately improve the interface between users and data, and borrows techniques from fields such as data management, systems, crowdsourcing, visualization, and HCI. Eugene Wu received his Ph.D. from CSAIL at MIT, advised by the esteemed Sam Madden and Michael Stonebraker, in the database group. He spent the first half of 2015 at UC Berkeley before starting at Columbia University in Fall 2015.