Research Interests
Deep Learning

This research focuses on deep reinforcement learning, convolutional neural network, and recurrent neural network to efficiently learn good controllers for specific tasks, and to automatically find specific structure in radar, image, and video signals.

Applications: autonomous flight control, object detection, path planning, model free control, electronic warfare modeling.


This research concentrates on applying and solving optimization problems, with an emphasis on theoretical and real-time implementation aspects. Our current research efforts are on the method for improving the speed of model predictive control using online optimization.

Applications: envelope protection control, skip trajectory optimization, missile guidance, wind farm control.

Kalman Filter and Beyond

This research investigates various application aspects of nonlinear filters such as extended Kalman filter, unscented Kalman filter, particle filter, IMM filter, and PDAF.

Applications: multi-sensor fusion, target tracking and data association, navigation and positioning system, fault detection and isolation, model identification.