Dr. Yiqun Xie, an assistant professor in Geospatial Information Science, recently co-led a comprehensive survey on hotspot detection techniques. The survey, published in ACM Computing Surveys, helps identify big-picture takeaways, research gaps and possible future directions in research on hotspot detection from a review of over 200 papers on the subject.

Detecting hotspots, or regions with significantly higher rates of generating cases of certain events, is important across a diverse range of sectors including public health, public safety, transportation, agriculture and more. In public health, for example, epidemiologists use spatial hotspots to identify disease outbreaks and reduce health risks to the public. Compared to traditional clustering, hotspot detection requires additional statistical rigor to remove spurious patterns in important societal applications.

Dr. Xie’s survey distills existing research on the topic into detailed taxonomies and summaries of models and algorithms, and proposes opportunities for future research approaches and applications. 


Learn more here. 



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