Rate My Professor David Levine

Levine's scholarly output features creative works such as High-fidelity control and optimization methods for power electronics systems (2018) and Comparison of Map Visualization Techniques Used for Spatial and Spatio-Temporal Data: An Analytical Survey Applied to COVID-19 Data, published in Medicinal Research Reviews. He has supervised master's theses addressing key areas in computing, including Panda Monitoring - a System to Monitor High Performance Computing Clusters (2007), Application of Software Engineering Best Practices and Tools to Small Development Teams (2006), Software Defined Load Balancing over an OpenFlow-Enabled Network (2017), and Data Discovery Analysis on Complex Time Series Data (2022). As Co-Principal Investigator, he contributed to grants like the GAANN - IOT program from the Department of Education and the UTA-FNAL CSE Master's Student Exchange Program sponsored by Fermi National Accelerator Laboratory. Levine also serves as faculty advisor for Google Developer Student Clubs at UTA, judges presentations at the Student Computing Research Festival, and supports departmental administration.