Amirezza is a Ph.D. student in Engineering Education at Purdue University. His research interests revolve around leveraging technology to enhance student learning experiences. He has significant experience in educational data mining and machine learning and is enthusiastic about designing computer-adapted testing to track students' abilities and skills, along with using Item Response Theory (IRT) models to analyze educational data. His research also extends to exploring technology-enhanced learning and its potential in improving student outcomes. Given his experience in operations research and optimization, his research examines the development and application of statistical algorithms to design educational systems that are both effective and efficient. Amirezza's goal is to use his expertise to contribute towards making a positive impact on education.