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Computer Science Faculty Helping Students Understand the Data Science of Risk and Human Activity

“The REU site will increase undergraduate student awareness, preparation, and interest in pursuing graduate degrees in STEM fields where data science is becoming a larger focus.” –Dr. George Mohler

The rapid growth of the Data Science field brings about an increase in the vast amount and variety of data that is produced.  Computer Science faculty members Dr. George Mohler and Dr. Mohammad Al Hasan serve as mentors to students conducting research through their National Science Foundation (NSF) Research Experiences for Undergraduates (REU) grant.  At just under $300,000, this 3 year grant will better prepare students seeking industry positions for the demands of companies where Data Science is a top priority. 

Last summer 8 undergraduate students were trained in data science methods, technologies, and applications and of this group of students 3 are pursuing STEM related graduate schools and 2 are employed at Software Engineers, both of which are IUPUI graduates.  Students have gained skills in research presentation, the creation of formal reports, and enhanced programming skills.  The student research topics will have an impact not only in Marion County but on a national scale as well.  One of the student projects is based on the prediction of space-time patterns of social harm. Dr. Mohler describes social harm as, "Events are broadly defined as events that are harmful to society and lead to a societal cost (crime, traffic crashes, drug overdoses, etc.)."  Mohler also explains that methods were created to predict the space-time risk of events and combine this risk estimate with an estimate of the societal monetary cost to create a dynamic social harm index that can be used to allocate resources (police, EMS, social service) to prevent or respond to social harm. This project is currently being continued through a NSF Smart and Connected Communities grant and a field trial is planned in spring 2019 in Indianapolis for algorithm guided dynamic policing and emergency medical services to address social harm.  Each group of students has conducted extensive research on various topics and has compiled copious amounts of data and created comprehensive reports on their findings and next steps in the research process.

 

 

 

Written By: Tiffany Essex (tielesse@iu.edu)