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The Intelligent Sensing & Perception Laboratory (ISP Lab) conducts research in a broad range of areas, including signal, image, and video processing; biomedical signal processing; statistical modeling; data science; traffic monitoring; computer vision; and sensor fusion for autonomous vehicles. More specifically, my research lies at the intersection of computer vision, machine learning, and statistical signal modeling, with a particular focus on developing learning-based approaches for sensor fusion and fundamental machine perception. The goal is to enable autonomous vehicle perception systems to operate reliably in diverse and challenging environments.
In addition, the ISP Lab pursues research in critical infrastructure monitoring, wildfire detection using multimodal sensors on UAV platforms, and human activity recognition with multimodal sensing. Other active research directions include brain–computer interface studies using EEG signal processing, as well as federated learning approaches designed to preserve the privacy of edge devices.
Interests
- Signal/Image/Video Processing
- Computer Vision
- Machine Learning
- Biomedical Signal Processing
- Statistical Modeling
- Autonomous Vehicles
- Sensor fusion
- Federate Learning
- Vision Language Models