AMPLab researchers Sanjay Krishnan, Prof. Michael Franklin, Prof. Ken Goldberg, Eugene Wu, and Jiannan Wang have developed ActiveClean, a system that uses machine learning to improve the process of removing dirty data by analyzing a user's prediction model to decide which mistakes to edit first, while updating the model as it works.  The demonstration paper titled "ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning" received the Best Demo Award at SIGMOD 2016.

ActiveClean is profiled in an I Programmer article and the development team led byEugene Wu (now at Columbia) will present its research on Sept. 7 in New Delhi, at the 2016 conference on Very Large Data Bases.