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Kenny Gruchalla leads the visualization efforts in the Computational Science Center at NREL. His current research is focused on developing interactive scientific visualization techniques that provide tools for finding meaning in increasingly large and complex data. Kenny has more than 25 years of professional experience in scientific programming and scientific visualization, spanning several scientific disciplines, including aerospace, geophysics, molecular biology, and environmental engineering. Gruchalla's dissertation work focused on the development of a general framework to define multi-scale, multivariate, non-Cartesian regions of interest in large-scale turbulent flow data. His master's thesis research evaluated scientific workflows in immersive virtual environments. His current research interests include scientific visualization, immersive visualization, GPU computing, human-computer interaction, and energy-systems analysis.

Research Interests

Scientific visualization

Immersive visualization

GPU computing

Human-computer interaction

Energy-systems analysis

Education

Ph.D., Computer Science, University of Colorado at Boulder

M.S., Computer Science, University of Colorado at Boulder

B.S., Computer Science, New Mexico Institute of Mining and Technology

Professional Experience

Senior Scientist, NREL Computational Science Center (2009–present)

Research Scientist, Red Canyon Engineering & Software (2003–2009)

Visitor, National Center for Atmospheric Research Data Analysis Services Group (2006–2008)

Professional Research Assistant, University of Colorado at Boulder (2001–2006)

Senior Analyst, United States Antarctic Program (2000–2001)

Senior Software Engineer, Raytheon (1995–2000)

Featured Work

The Utility of Virtual Reality for Science and Engineering (Chapter 21), VR Developer Gems (2019)

Visualizing the Impacts of Renewable Energy Growth in the U.S. Midcontinent, IEEE Open Access Journal of Power and Energy (2020)

Enabling Immersive Engagement in Energy System Models with Deep Learning, Statistical Analysis and Data Mining: The ASA Data Science Journal (2019)

A Simulation Study Demonstrating the Importance of Large-Scale Trailing Vortices in Wake Steering, Wind Energy Science (2018)

Eastern Renewable Generation Integration Study, NREL Technical Report (2016)

Evaluating the Efficacy of Wavelet Configurations on Turbulent-flow Data, IEEE 5th Symposium on Large Data Analysis and Visualization (2015)

Immersive Well-path Editing: Investigating the Added Value of Immersion, IEEE Virtual Reality (2004)