Location
Link Lab 277 (2nd floor Olsson Hall)
Lab
​Olsson 008 151 Engineer's Way
UVA Engineering Link Lab

About

Laura Barnes is a professor in the Department of Systems and Information Engineering. She is the Associate Director of Link Lab and directs the Sensing Systems for Health Lab which focuses on designing impactful, technology-enabled solutions for improving health and well-being. She received her Ph.D. degree in computer science from the University of South Florida. Laura’s work has been funded by the National Institutes of Health, National Institute of Aerospace, US Army, and private foundations.

Education

B.S. Computer Science, Texas Tech University, 2003

M.S. Computer Science, University of South Florida, ​2007

Ph.D. Computer Science, University of South Florida, 2008

"My research leverages mobile and wearable wireless technologies capable of real-time monitoring to better understand human behavior in natural environments."

Laura Barnes, professor

Research Interests

Autonomy and Controls/Control Systems
Wireless Health
Human Machine Interface
Biomedical Data Sciences
Machine Learning

Selected Publications

“Near-Optimal Incentive Allocation for Piggyback Crowdsensing”. In: IEEE Communications Magazine 55.7 (2017), pp. 120-125. H. XIONG, D. ZHANG, G. CHEN, Z. GUO, V. GAUTHIER, AND L. E. BARNES.
“Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students”. In: J Med Internet Res 19.3 (2017), e62. P. CHOW, K. FUA, Y. HUANG, W. BONELLI, H. XIONG, L. E. BARNES, AND B. TEACHMAN.
"Spanish-Language Consumer Health Information Technology Interventions: A Systematic Review”. In: J Med Internet Res 18.8 (2016), e214. A. CHAET, B. MORSHEDI, K. WELLS, L. E. BARNES, AND R. VALDEZ.
“iCrowd: Near-Optimal Task Allocation for Piggyback Crowdsensing”. In: IEEE Transactions on Mobile Computing 15.8 (2016), pp. 2010-2022. H. XIONG, D. ZHANG, G. CHEN, L. WANG, V. GAUTHIER, AND L. E. BARNES.
“Daehr: a Discriminant Analysis Framework for Electronic Health Record Data with its Application to Early Detection of Mental Health Disorders”. In: ACM Transactions on Intelligent Systems and Technology 8.3 (2016), 1-21. H. XIONG, J. ZHANG, Y. HUANG, K. LEACH, AND L. E. BARNES.