Namkyoung Lee

• Build fleet-scale EV health monitoring systems that turn telemetry, service, and manufacturing data into diagnostics, PHM alerts, and reliability decisions. • Define Vehicle Health Management requirements across EV systems and service workflows. • Develop alerts for thermal, chassis, electromechanical systems. • Build Spark/Airflow workflows for fleet management systems. • Support diagnostics, risk assessment, and field-quality decisions using telemetry, service, and manufacturing traceability data.

• Developed safety-critical PHM and anomaly detection algorithms for electromechanical systems, with focus on diagnostics, prognostics, and degradation monitoring. • Built ML-based methods to detect abnormal electrical behavior and predict degradation trends. • Supported applied PHM research for automotive/electromechanical systems. • Co-instructed a University of Maryland graduate course on AI, reliability, and Prognostics & Health Management.

• Developed interpretable ML, signal-processing, and physics-of-failure methods for diagnostics, prognostics, and failure analysis of electromechanical systems. • Built TensorFlow-based neural network layers to improve physical interpretability of learned diagnostic features. • Developed data-driven and physics-of-failure-based PHM methods for automotive components, electric circuits, and semiconductor manufacturing equipment. • Conducted field-data failure analysis, including statistical analysis and root-cause investigation of IGBT failures. • Built MATLAB PHM software with an interactive GUI for developing and applying data-driven health monitoring methods. • Delivered lectures and webinars on data-driven PHM, reliability, and product qualification at the University of Maryland and Hong Kong Polytechnic University.

• Developed deep learning and robotics-based indoor positioning systems using magnetic signals, Wi-Fi sensing, LiDAR SLAM, and ROS. • Built a CNN-based magnetic indoor positioning algorithm to improve location estimation in indoor environments. • Developed an automatic Wi-Fi signal collection system using LiDAR SLAM and ROS. • Improved indoor localization accuracy using Cisco wireless infrastructure data. • Conducted research at the intersection of indoor positioning, sensor fusion, robotics, and machine learning.

• Managed UPSs’ (Uninterruptable Power Supply) domestic & international certifications (CE, UL and etc.) • Managed product specification translation