Bio

B.S. Computer Science, Texas Tech University, 2003M.S. Computer Science, University of South Florida, ​2007Ph.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

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.

Research Interests

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

In the News

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.
  • “DEMONS: An Integrated Framework for Examining Associations Between Physiology and Self-reported Affect Tied to Depressive Symptoms". In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct. ACM, 2016. P. Chow, W. Bonelli, Y. Huang, K. Fua, B. A. Teachman, and L. E. Barnes.
  • “SAD: Social Anxiety and Depression Dynamic Monitoring System”. In: Computing and Mental Health Workshop, CHI: ACM Conference on Human Factors in Computing Systems. 2016, pp. 1-4. P. Chow, K. Fua, H. Xiong, W. Bonelli, B. Teachman, and L. E. Barnes.
  • “Assessing Social Anxiety Using Gps Trajectories and Point-of-interest Data”. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 2016, pp. 898-903. Y. Huang, H. Xiong, K. Leach, *Y. Zhang, P. Chow, K. Fua, B. A. Teachman, and L. E. Barnes.
  • “Sensus: A Cross-platform, General- purpose System for Mobile Crowdsensing in Human-subject Studies”. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 2016, pp. 415-426. H. Xiong, Y. Huang, L. E. Barnes, and M. S. Gerber.