Penny Atkins is currently making significant contributions as a Graduate Research Assistant at the University of Utah, where she is deeply involved in the One Utah Data Science Hub. This initiative plays a pivotal role in integrating various data science projects, including the Data Exploration...
Penny Atkins is currently making significant contributions as a Graduate Research Assistant at the University of Utah, where she is deeply involved in the One Utah Data Science Hub. This initiative plays a pivotal role in integrating various data science projects, including the Data Exploration and Learning for Precision Health Intelligence (DELPHI) and the Data Science and Ethics of Technology (DATASET). Through her work, Penny is at the forefront of advancing data science research and education, particularly in the context of precision health and biomechanics.
Her expertise lies in both experimental and computational methodologies, which she applies to her research on the biomechanical relationships between anatomical shapes and their functional implications. Penny employs a variety of advanced techniques, including motion capture, statistical shape modeling (SSM), and finite element analysis (FEA), to analyze complex biomechanical systems. Her proficiency in data analysis and time-lapsed imaging further enhances her ability to derive meaningful insights from intricate datasets.
In her role, Penny is not only focused on her research but also actively engages in collaborative projects that aim to improve healthcare outcomes through innovative data science applications. Her skills in design of experiments, statistical analysis, and programming languages such as Python and MATLAB enable her to tackle complex problems with a creative and analytical approach. As a Six Sigma Green Belt, she applies principles of Lean Manufacturing and Agile Project Management to streamline research processes and enhance efficiency. Overall, Penny Atkins is a dedicated researcher whose work is poised to make a lasting impact on the fields of orthopaedics and data science.
