Rate My Professor Zeyar Aung

Dr. Zeyar Aung is an Associate Professor in the Department of Computer Science at Khalifa University. He earned his Ph.D. in Computer Science from the National University of Singapore in 2006 and his Bachelor of Computer Science with First Class Honors from the University of Computer Studies, Yangon, in 1999. Prior to joining Khalifa University, he served as a Research Fellow at the Institute for Infocomm Research, A*STAR in Singapore from 2006 to 2010. He joined Masdar Institute as an Assistant Professor in 2010, which later became part of Khalifa University, and was promoted to Associate Professor in 2015. He also held a Visiting Scholar position at the Massachusetts Institute of Technology in 2010 and worked as an Analyst-Programmer in Myanmar from 1999 to 2000.

Dr. Aung’s research focuses on machine learning, data analytics, data science, big data, cybersecurity, computational sustainability, wireless sensor networks and IoT, and applications in renewable energy and smart grids. His earlier work centered on bioinformatics, chemoinformatics, and spatio-temporal data analysis. He is a Senior Member of IEEE and has received several honors, including the Certificate of Commendation for Faculty Service Excellence from Khalifa University in 2019, Best Paper Awards at conferences in 2012 and 2014, and the Dean’s Graduate Award from the National University of Singapore in 2005. He has authored or co-authored numerous publications in journals and conferences on topics such as watermarking in databases, road network extraction from satellite images, Twitter analysis for happiness patterns, malware behavior clustering, electricity price forecasting, and data mining for job market requirements. He serves as an associate editor for journals including the International Journal of Advanced Computer Research and the Journal of Ambient Intelligence and Humanized Computing, and has reviewed for many leading publications in computer science and related fields. He teaches courses including Introduction to Computing Using C++, Foundations of Computer Science, Introduction to Machine Learning, and Data Science.