3. Research Interests

Current Interests

• Artificial intelligence

• Machine learning

• Quantum-assisted communication

• Internet of Things

• Vehicular networks

• 5G wireless communications

• Edge computing, fog computing and cloud computing

• Information centric networking, software defined networking and network function virtualization

Past Interests

• Scheduling and resource allocation in stochastic networks

• Internet of things (IOT over LTE/LTE-A network, cyber-physical systems, big data, distributed

sensing and control)

• Time series analysis and dynamic factor models (stationary and non-stationary)

• Wireless communications and networking

• Cognitive radio (full-duplex communications, software defined radio architectures, protocol design,

spectrum sensing, detection and estimation)

• Statistical signal processing, compressed sensing, and compressive sampling

• Random matrix theory

Human action recognition for smart health monitoring

EdgeAI-empowered Data Communication, Processing and Control for Military Operations

1) AI-enabled Framework for Communication and Computing.

2) AI-empowered Framework for NextG Network Slicing.

3) AI-enabled Secure, Privacy preserving and Trustworthy Computing Services.

KPIs: spectrum utilization, spectrum risks, latency, high density of connections, efficiency, agility, reliability and security.

AI aided Communication and Computing Resource Allocation to Support Blockchain-enabled Video Streaming

1. Improve operating efficiency and maximize transcoding rewards.

2. Model vehicular mobility by highly-realistic Semi-Markov renewal process.

3. Propose multi-timescale actor-critic-reinforcement learning framework to tackle challenges of dynamic variants of environment, resources, mobility & real-time video service delay.

4. Propose mobility-aware estimation for large timescale model.

5. Enhance mobility prediction performance by using analysis and classical ML.