Josahandi Cisneros-Sherman

Josahandi Cisneros-Sherman

Research

Higher Education and the Automation of Inequality through “Inattentional Blindness” : Survey Study

Published in , 2022

“Inattentional blindness” refers to the phenomenon of algorithmic biases that emerge when the system developers fail to capture the desired complex real-world goals in their target variables and problem specifications procedures. As such, the main objective of this study was to examine the materialization of this phenomenon in higher education. And investigate if the pattern of “inattentional blindness” currently aggravating the technology industry, is also observed among the diverse student body of a public, four-year, federally designated Hispanic Serving Institution (HSI).

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Reducing Racial Bias by Information Maximization Adaptation Network: A Review

Published in , 2022

Motivated by the recent surge in research dedicated to the mitigation of racial bias in deep-learning based Facial Recognition(FR) systems, this investigation focused on an assessment and architectural implementation of Information Maximization Adaptation Network(IMAN), a promising Unsupervised Domain Adaptation (UDA) approach that addresses racial bias through transfer recognition knowledge that addresses racial bias through transfer recognition knowledge from the “Caucasian ” race-category as source domain and other races such as ‘African’, ‘Asian’, and ‘Indian’ as target domains.

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