Dr. Bosman has a Ph.D. in Industrial Engineering. Her research interests include Decision Support Systems (e.g., solar energy performance, valuation, and management) and Engineering Education (entrepreneurial mindset, energy education, interdisciplinary education, and faculty professional development). She spent the first part of her career working as a manufacturing engineer for world-class companies including Harley-Davidson, John Deere, and Oshkosh Defense and continues to provide workforce development consulting within this area.
Dr. Madamanchi is an independent Postdoctoral Researcher in the Future Work and Learning strategic impact area of Purdue University Polytechnic. His research centers around supporting digital transformation through workforce development, with a special focus on data science education and AI literacy.
Scott R. Bartholomew, PhD. is an assistant professor of Engineering/Technology Teacher Education at Purdue University. Previously he taught Technology and Engineering classes at the middle school and university level. Dr. Bartholomew’s current work revolves around Adaptive Comparative Judgment (ACJ) assessment techniques, student design portfolios, and Technology & Engineering teacher preparation.
Dr. Vetria L. Byrd is an assistant professor in the Department of Computer Graphics Technology in the Polytechnic Institute at Purdue University in West Lafayette, Indiana. Dr. Byrd is the founder and organizer of the biennial Broadening Participation in Visualization (BPViz) Workshop. Dr. Byrd has given numerous invited talks on visualization and has been featured in HPC Wire online magazine (2014), and numerous workshops nationally and internationally. Dr. Byrd received her graduate and undergraduate degrees at the University of Alabama at Birmingham, in Birmingham, Alabama which include: Ph.D. in Computer and Information Sciences, Master’s degrees in Computer Science and Biomedical Engineering and a Bachelor’s degree in Computer Science. Dr. Byrd’s research interests include: data visualization, data visualization capacity building and pedagogy, high performance visualization, big data, collaborative visualization, broadening participation and inclusion.
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