NCSI: Geospatial Clustering and Community Characterization for Suicide Risk Management

Status	Completed
Mentor Name	Xinlian Liu
Mentor's XSEDE Affiliation	Campus Champion Fellow, Education Allocation
Mentor Has Been in XSEDE Community	4-5 years
Project Title	Geospatial Clustering and Community Characterization for Suicide Risk Management
Summary	The suicide rate in the US increased by 30% in the past decade. It has become a leading cause of death. Predicting suicide or suicide attempts are difficult. Community-based preemptive interventions have the potential to help targeted groups of high-risk people. This approach relies on the accurate characterization of suicide clusters and the timely monitoring of suicide clusters. We have developed some preliminary models with promising results.
Job Description	1) Literature review and methodology development; 2) Data collection, exploration, normalization; merging heterogeneous data sets from different sources. 3) Training neural networks and scale-up computation.
Computational Resources	Bridges
Contribution to Community
Position Type	Apprentice
Training Plan	Must have organized computational research internship experiences; experiences of working with supercomputers; experiences with Geospatial analysis; experiences with working with large datasets; Python programming; Deep Learning
Student Prerequisites/Conditions/Qualifications	A strong motivation to serve the country and the people through conducting an impactful research project. We collaborate closely with DOE and VA. Apprentices are expected to have strong communication skills.
Duration	Semester
Start Date	09/16/2019
End Date	12/15/2019