An Exploration of H-1B Visa Applications in the United States
This work addresses a problem for US businesses and educational institutes in recruiting foreign talent, but it appears incremental as it builds on existing methods without clear novelty.
The paper tackled the problem of predicting H-1B visa application certification outcomes by performing exploratory data analysis and training classifiers, but no concrete performance numbers or results were provided in the abstract.
The H-1B visa program is a very important tool for US-based businesses and educational institutes to recruit foreign talent. While the ultimate decision to certify an application lies with the United States Department of Labor, there are signals that can be used to determine whether an application is likely to be certified or denied. In this paper we first perform a data-driven exploratory analysis. We then leverage the features to train several classifiers and compare their performance. Finally, we discuss the implications of this work and future work that can be done in this area.