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One prominent example is Maksim, a college student from Maryland who dedicated his spring break—spending eight to ten hours daily—to developing tools that could facilitate better understanding of the data. His innovation involved creating an algorithm that clusters academic articles by topic, employing a technique known as dimensionality reduction.
By plotting the similarities between papers, Maksim’s approach reveals relationships that might escape human sight. For instance, clusters are identified around key subjects such as MERS, social and economic impacts, face masks, and filtration. These visualizations enable researchers to spot patterns and connections, informing targeted research and decision-making.