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Although different organizations have defined policies towards diversity inacademia, many argue that minorities are still disadvantaged in universityadmissions due to biases. Extensive research has been conducted on detectingpartiality patterns in the academic community. However, in the last fewdecades, limited research has focused on assessing gender and nationalitybiases in graduate admission results of universities. In this study, wecollected a novel and comprehensive dataset containing information onapproximately 14,000 graduate students majoring in computer science (CS) at thetop 25 North American universities. We used statistical hypothesis tests todetermine whether there is a preference for students' gender and nationality inthe admission processes. In addition to partiality patterns, we discuss therelationship between gender/nationality diversity and the scientificachievements of research teams. Consistent with previous studies, our findingsshow that there is no gender bias in the admission of graduate students toresearch groups, but we observed bias based on students' nationality.

Diversity dilemmas: uncovering gender and nationality biases in graduate admissions across top North American computer science programs