A researcher may be evaluated based on several measures such as the total number of published papers, number of citations, and her/his h-index. These measures may not reflect the real quality of researchers as many self citations and citing co-authors are observed during last decades. On the other hand, having a realistic quantitative measure for scientists has enormous impact on decisions taken in academia including hiring and promoting faculty members. This research aims to develop a mathematical model for evaluating scientific researchers. The model uses authors' interactions and provides a quantitative value as a proxy of author’s quality. There are two existing models named R-model and Q-model for the same purpose. Our proposed model improves on these models by incorporating an iterative strategy to obtain best quantitate evolution of the researchers. Practically, we have tested our model on DBLP dataset.
I've done my B.Sc. project under Dr. Motahari's supervision.