Research

AI assisted Wireless System Design and Optimization

  • Novel design of deep-learning and convolutional neural network approaches for wireless system applications and services.
  • Novel design of machine-learning and pattern recognition algorithms for wireless communication technologies.
  • Applications of AI for optimizing wireless communication systems, including channel models, channel state estimation, beamforming, code book design and signal processing.
  • Applications of AI for 5G and 6G wireless transmission technologies, including coordinated multiple points transmission/reception, large scale antenna array, and multi-hop relay.
  • Applications of AI for 5G and 6G mobile management, including user association, handoff strategy, and backhaul technology.
  • Applications of AI for 5G and 6G resource management, including spectrum resources, energy sources, cloud resources, computing resources, and communication infrastructure.
  • The analysis and prediction of 5G and 6G network behaviour via AI technologies, including the multi-media traffic load, network overhead, and network collision.
  • Evaluating the scope for and potential limitations of AI solutions in wireless communications.

AI based Cellular System Design

AI based IoT System Design

Information Theory

  • Network information theory: Investigation on the fundamental limits and practical code design for data transfer and compression in multi-user networks
  • Cache aided networks: Investigation on the fundamental limits and network coding of cache aided content delivery networks
  • Joint source–channel coding: Joint source–channel coding architecture design for efficient description of multiple sources over noisy networks with applications to sensor networks
  • Computation over networks (compute–forward): Investigation on the fundamental limits and practical code design of distributed computation over interference and multihop networks
  • Network optimization for drones and vehicles: Optimal network resource allocation and base station placement for drone and vehicle networks
  • Machine learning based communication techniques: Creating new communication architec- tures and protocols bases on deep learning and reinforcement learning

AI-5G/6G System Implementation

  • Enabling 5G PHY Research through Prototyping: Developing PoC (Proof-of-Concept) using open SDR (software-defined-radio) products, USRP
  • AI in Communication Systems Physical Layers: Applying AI to end-to-end communication systems, massive MIMO with AI, spectrum sharing with AI
  • Autoencoder based modems for next generation communication systems

Machine-Learning for Medical Imaging

  • Segmentation of MRI brain scans for tumor detection
  • Generative adversarial networks for data augmentation in MRI brain scans

Data augmentation for brain MRI

Medical Image Segmentation for Tumor Detection