Rate My Professor Elizabeth Diaz

Elizabeth D. Diaz is an Associate Professor of Instruction in the Computer Science and Engineering Department at the University of Texas at Arlington, where she has served on the faculty since 2016. Initially appointed as a Senior Lecturer, she has advanced in her instructional role, emphasizing excellence in teaching within computer science. Diaz instructs core courses such as Data Mining, Web Data Management, and Mobile Application Development. Her teaching has directly impacted student innovation, notably in 2020 when her guidance enabled students to create a web application for international job applications amid the COVID-19 disruptions, as highlighted in university news.

Diaz's research interests include machine learning, neural networks and deep learning, data mining under artificial intelligence, software design under software engineering, and mobile development applications. She has advised graduate theses, such as Nilav Bharatkumar Patel's 'Extractive Summarization and Simplification of Scholarly Literature' in May 2020 and a project on 'Semi-supervised Learning using Triple-Siamese Network' in 2020. As a member of the editorial board for Discover Internet of Things by Springer Nature, she contributes to the field. Key publications feature 'IoT device for detecting abnormal vibrations in motors using TinyML' in Discover Internet of Things (2025), where she contributed to the design, and 'Artificial Intelligence in Clinical Applications of Helicobacter pylori: A Comprehensive Review' in IEEE MedAI proceedings (2025). Diaz has moderated sessions at the Athens Institute for Education and Research conferences, including the 2024 Computing Symposium, represented her department at the Grace Hopper Celebration in 2018, and served as a faculty mentor in the Center for Research on Teaching and Learning Excellence during 2018-2019.