Research & Innovation | School of Electronic Engineering

AI & Machine Learning Image
AI & Machine Learning

AI & Machine Learning

Artificial Intelligence (AI) is concerned with getting computers to perform tasks that currently are only feasible for humans. Within AI, Machine Learning aims to build computers that can learn how to make decisions or carry out tasks without being explicitly told how to do so. We conduct innovative research in all areas of Artificial Intelligence & Machine Learning including:

  • Deep Neural Nets
  • Deep Learning
  • Natural Language Processing (see Computational Linguistics Group)
  • Semantics, Ontologies and Reasoning
  • Multi-Agent Systems
  • Recommender Systems

 

Faculty Members

Ali Intizar

Mingming Liu

Derek Molloy

Kevin McGuinness

Noel Murphy

Noel O'Conor

Paul Whelan

 

Comms Networks and Future Comms
Comms Networks and Future Comms

Comms Networks and Future Comms

Advanced networking technology provides the lines that support today’s online services. The growing demand for video streaming and video conferencing, cloud computing, smart homes and cities, phone payments and decentralised finance, and many other services that require network connectivity spurs our research into future communications networks.

Our team explores such topics as enhancing wireless bitrates using Multi-Input, Multi-Output (MIMO) communications and improved models of radio wave propagation, and delivering wireless services in challenging environments such as inter-vehicle communication (IVC). In fixed or “tethered” networks, we explore optimising the design and interconnection of such network resources as switches and routers in data centres and the wider Internet.

Our research also involves developing and enhancing the network protocols that support all the services and applications delivered over today’s and tomorrow’s wireless and fixed networks.

We conduct innovative research in all areas of Comms Networks and Future Comms including:

  • 5G+
  • Data Networks
  • Wireless Communications

 

Faculty Members

Prince Anandarajah

Liam Barry

Dushyantha Basnayaka

Connor Brennan

Martin Collier

Conor McArdle

Jennifer McManis

Gabriel Miro Muntean

Xiaojun Wang

 

Computer Vision
Computer Vision

Computer Vision

Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects, and then react to what they “see.”

We conduct innovative research in all areas of Computer Vision including:

  • Image Processing & Analysis
  • Industrial Vision
  • Consumer
  • Biomedical
  • 3D Visualization
  • Augmented Reality for home rehab and sports performance

 

Faculty Members

Shirley Coyle

Derek Molloy

Kevin McGuinness

Noel O Connor

Robert Sadleir

Paul Whelan

Connected Embedded Devices/IoT
Connected Embedded Devices/IoT

Connected Embedded Devices/IoT

The Internet of Things (IoT) is a computing concept describing the interconnectivity and collaboration of a wide variety of everyday physical objects connected via the Internet. Rapid IoT development has been driven by ongoing research and technological advances (notably in 5G mobile communications and in Artificial Intelligence). IoT technologies are enabling a wide range of business opportunities in the context of “smart” homes, neighbourhoods and cities and in the exploitation of intelligent infrastructure and services, in areas such as transport, power and healthcare.

We conduct innovative research in all areas of Connected Embedded Devices/IoT including:

  • IoT Devices
  • Systems & Analytics
  • Built environment sensing
  • IoT Networking
  • Security & Privacy

 

Faculty Members

Martin Collier

Stephen Daniels

Ali Intizar

Mingming Liu

Conor McArdle

Derek Molloy

Robert Sadleir

Xiaojun Wang