Đức Long Lê

Designed an end-to-end ML pipeline to detect IoT network intrusions utilizing the comprehensive CICIoT2023 dataset. Executed large-scale data preprocessing, feature engineering, and multi-level attack labeling to prepare raw network flows. Benchmarked classical ML, deep learning, and Transformer-based models to optimize performance under severe class imbalance.

ML Engineer Intern – Network Intrusion Detection - Motorola Solutions Vietnam R&D Center - Ho Chi Minh City, Vietnam

(2025-10 - 2025-12)

• Designed an end-to-end ML pipeline to detect IoT network intrusions utilizing the comprehensive CICIoT2023 dataset.
• Executed large-scale data preprocessing, feature engineering, and multi-level attack labeling to prepare raw network flows.
• Benchmarked classical ML, deep learning, and Transformer-based models to optimize performance under severe class imbalance.
• Analyzed experimental results against state-of-the-art research and presented technical findings to senior R&D mentors.

B.S. - Information Technology - University of Management and Technology in HCM