George V. Kondraske is a professor of electrical engineering and bioengineering at the University of Texas at Arlington (UTA). He is also the founding director of the Human Performance Institute at UTA. He received a B.S. in electrical engineering from the University of Rochester and the M.S. and Ph.D. degrees from The University of Texas at Arlington – University of Texas Southwestern Medical Center joint program in biomedical engineering. He joined the faculty at UTA in 1982. His research has been aimed at a quantitative understanding of the relationship between human systems and tasks from the perspective of performance. He developed an array of instruments and methods to measure different aspects of human perfomrance, including information processing, sensory, and neuromotor performance capacities. He introduced General Systems Performance Theory (GSPT) and applied it to the human system to realize the Elemental Resource Model (ERM) for human performance. This resulted in the development of new performance modeling and predictive analytic methods known as Nonlinear Causal Resource Analysis (NCRA). More recently, he has applied GSPT and other performance measurement concepts to web-based measurement tools, including the commercial product known as RC21X (a brain performance capacity measurement tool for self- or supervised administration) Research has been sponsored by NIDRR, NSF, NASA, DOE, USAF, NIH, the Veterans Administration, as well as private foundations and companies. He has authored over 250 published works, served as Section Editor for the “Human Performance Engineering” section of The Biomedical Engineering Handbook (CRC Press), and holds several patents. He was awarded the Institute of Electrical and Electronics Engineers (IEEE) "Engineering in Medicine and Biology Society Early Career Award", the Association for the Advancement of Medical Instrumentation "Becton-Dickinson Career Achievement Award", is a Fellow of the IEEE and a charter fellow of the National Academy of Inventors. Dr. Kondraske has expertise in human and system performance measurement and modeling, predictive analytics, assistive technologies, sensor and instrumentation design, and measurement systems.
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