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Geospatial Inspired Community Characterization with High Dimensional Data (Learner Position)


Shodor > NCSI > XSEDE EMPOWER > XSEDE EMPOWER Positions > Geospatial Inspired Community Characterization with High Dimensional Data (Learner Position)

Status
Completed
Mentor NameXinlian Liu
Mentor's XSEDE AffiliationCampus Champion
Mentor Has Been in XSEDE Community4-5 years
Project TitleGeospatial Inspired Community Characterization with High Dimensional Data (Learner Position)
SummaryWe have been studying the geospatial clustering of high-dimensional data for health risk management. In particular, we are interested to find out the impact of various social determinants on residents' overall mental health for a community. We approach this problem from three directions: 1) geostatistics, 2) graph learning, 3) visualization
Job DescriptionGathering and pre-processing data from CDC, US Census, and other sources.
Coding
Documentation
Computational ResourcesStampede at TACC
Contribution to CommunityOur study will offer insight into how to improve healthcare through innovative approaches
Position TypeLearner
Training PlanMentor guided reading and collaboration
Student Prerequisites/Conditions/QualificationsMust have: 1) Python; 2) Statistics; 3) Linux command line Desirable: 1) PyTorch, 2) visualization experience, 3) Parallel programming
DurationSemester
Start Date09/01/2021
End Date12/15/2021

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