HPC enabled ML-based approaches for Veteran Suicide Prevention

11/6/2019
By Xinlian Liu, Hood College, Frederick, Maryland

Abstract:
Suicide is a national health crisis and a leading cause of death in the US.  The suicide rate for veterans is much higher than civilians.  The Department of Energy and the Department of Veterans Affairs launched a joint project to tackle this challenging problem by combining the power of supercomputing and the promise of big data.  We will discuss our approaches in building predictive models for suicide prevention and our efforts from public health perspectives.

About the Speaker:
Xinlian Liu is an Associate Professor at Hood College in Frederick, Maryland in the United States.  He received a B.S. in Computer Engineering from Huazhong University of Science and Technology in China and a Ph.D. in Computer Science from Louisiana State University.  He worked on theories and applications of distributed systems at the National Meteorological Center, Cray Research, and Argonne National Lab.  In addition to teaching, he is a Visiting Faculty at the Berkeley National Lab and a Guest Scientist at the National Cancer Institute.  Xinlian Liu is a Fulbright Scholar in Data Science, hosted by Dr. Rui Oliveira.

LOCATION AND TIME

Address:  University of Minho, Gualtar Campus, Braga, Portugal

Building: Departamento de Informatica, Building 07

Networking Session: 01:45 PM, Meeting Room, 3rd floor

Talk Session: 02:00 PM, Meeting Room, 3rd floor
 

PHOTOS