Research Interests

I am interested in communication theory and signal processing with emphases on coding, wireless communications, image processing, and wireless networks.

I have been working on the theoretical and practical challenges of designing communication systems and networks that use multiple antennas and/or relays, especially in the presence of interference. There are many challenges in designing space-time coding and beamforming schemes for multiple-input multiple-output (MIMO) systems and designing distributed methods for cooperative communications especially in the presence of interference. One of these challenges is to study the theoretical tradeoffs and limits from an information theory perspective. Another is to design practical coding and beamforming schemes that satisfy those limits using signal-processing methods.

On a related topic, I have been looking at optimizing resources across different layers of a wireless network. This is in particular important for mobile ad-hoc networks and wireless sensor networks where the traditional layer hierarchies may not exist. I am interested in cross-layer adaptation, network connectivity, power-aware wireless network protocols, cooperative communications, and interference cancellation especially for networks with multiple-antenna nodes and relays.

Also, I have been involved in developing data compression algorithms especially for image and video coding. My recent work in this field concerns the transmission of multimedia information over wireless networks and the Internet. A related topic of interest is the image/video quality estimation especially for a heterogeneous network that supports different resolutions and bandwidth. I am interested in developing new coding schemes and network protocols that improve end-to-end recovery and enhance the quality of service.

Multiscale Image Quality Estimator (MIQE) Software is available here

Multiscale Video Quality Estimator (MVQE) Software is available here

In addition, I have worked on segmenting cardiac images, especially MRIs, using traditional image processing algorithms and learning-based methods.

Every Important Idea Is Simple !

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