MR. ERZA

Biography

MR. ERZA received the bachelor and Master degrees in electrical engineering from the Bandung Institute of Technology (ITB), Indonesia, in 2013 and 2014, respectively, and the Ph.D. degree from the School of Computing, Korea Advanced Institute of Science and Technology (KAIST), South Korea, in 2018. KAIST is consistently ranked among the top-20 universities worldwide for Computer Science. His dissertation was about the leverage of state-of-the-art artificial intelligence model for detecting threats in Wi-Fi networks. His doctoral research focused on the intersection of cybersecurity and artificial intelligence, an area of increasing importance in today’s digital landscape. This research has been recognized through publications in esteemed journals and conferences such as IEEE Information Forensics and Security, IEEE Access, ACM CCS Conference, and IEEE Privacy Security and Trust, among others. He is currently an Assistant Professor with Monash University Indonesia, Cyber Security program. Also, he is the program coordinator of the Master of Cyber Security program.
He was a post-doctoral researcher at National Institute of Information and Communications Technology (NICT), Tokyo, Japan in AI x Security and a lecturer at University of Indonesia (UI) in cyber-crime. He was accounted for developing a machine-learning-based filter to reduce the number of intrusion alerts pooled worldwide by the Network Incident analysis Center for Tactical Emergency Response (NICTER). One highlighted output is a machine learning model that can reduce almost 90% of un-important threat alerts among Billions of alerts in a day. He is also a Senior Research (Data) Scientist at Jakarta Smart City and advisory board for several government and private organisations. As a data scientist, his duties are to conduct business understanding, formulate research questions, machine learning modeling, and deployment. In Jakarta Smart City, he cover all Jakarta Province Bodies’ data for reports, visualizations, lesson-learned and predictions. One highlighted output is a predictive model to measure COVID-19 mortality based on clinical features. He wrote a book entitled: “Network intrusion detection using deep learning: a feature learning approach” which published by Springer. His current research interests include information security, artificial intelligence, anomaly detection, intrusion detection, cybersecurity, digital transformation and smart city.