A Deep Learning-Based Approach for Predicting the Outcome of H-1B Visa Application

  • Anay Dombe
  • Rahul Rewale
  • Debabrata SwainEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1101)


The H-1B is a visa that allows US employers to employ foreign workers in specialty occupations. The number of H-1B visa applicants is growing drastically. Due to a heavy increment in the number of applications, the lottery system has been introduced, since only a certain number of visas can be issued every year. But, before a Labor Condition Application (LCA) enters the lottery pool, it has to be approved by the US Department of Labor (DOL). The approval or denial of this visa application depends on a number of factors such as salary, work location, full-time employment, etc. The purpose of this research is to predict the outcome of an applicant’s H-1B visa application using artificial neural networks and to compare the results with other machine learning approaches.


H-1B Labor condition application Deep learning Artificial neural networks 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Vishwakarma Institute of TechnologyPuneIndia

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