Ben Birnbaum stood for his general exam last week, on a topic that I’m very interested in:
ABSTRACT–
Surveys are one of the principal means of gathering critical data from low-income regions. However, interviewer fabrication, or curbstoning, can threaten data quality. The existing literature lacks a set of general-purpose techniques to detect curbstoning; it does not capitalize on the potential of mobile data collection tools to help detect the phenomenon; and it provides few rigorous validations of the techniques that are developed. In this talk, I propose an anomaly detection framework to develop several general-purpose algorithms that identify curbstoning.
These algorithms can take advantage of the information in user traces from mobile data collection, a potential that I will evaluate rigorously. I also propose two studies to obtain high-quality labeled data sets with which I will validate my algorithms, thus partially filling the need for more rigorous evaluations.
Good job, Ben! Also in attendance was Aram Harrow, who was reminded of this great story of the lying professor. I wonder, could I could pull that off?
Healthy Algorithms 