Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks
(With Avishek Kumar, Ali Rizvi, Benjamin Brooks, R. Ali Vanderveld, Chad Kenney, Sam Edelstein, Adria Finch, Andrew Maxwell, Joe Zuckerbraun, Rayid Ghani.)
We build a model to predict which water mains will break in the coming year in Syracuse, NY. We perform quite well, and the model is being used to guide proactive water main repair.
Estimating student proficiency: Deep is not the panacea
(With Xiong, X., Khajah, M., Lindsey, R.V., Zhao, S., Karklin, Y., Van Inwegen, E.G., Han, B., Ekanadham, C., Beck, J.E., Heffernan, N., Mozer, M.C..)
Workshop on Machine Learning in Education @ NIPS'16.
A summary of three distinct critiques of Deep Knowledge Tracing as a method of estimating student proficiency.
Correlations of Partial Words
(With Francine Blanchet-Sadri, Joshua D. Gafni.)
A Report on Felony Crime in the District of Columbia in 2016
As Office of the Deputy Mayor for Public Safety and Justice of the District of Columbia.
(With Eric Foster-Moore and Paul Testa.)
Council of the District of Columbia January 2018.
A summary of felony crimes (mandated by law) in the District of Columbia in 2016.
The Knewton Platform: A General-Purpose Adaptive Learning Platform
(With Zachary Nichols.)
A deep dive into how Knewton's online learning platform worked at the time.
Reducing the Gap: How Adaptive Follow-Ups Help Struggling Students
(With Hillary Green-Lerman and David Kuntz.)
Online October 2015.
A retrospective study exploiting variation in who used the Knewton platform to determine the effects of immediate, targeted follow ups on proficiency.