Motion recognition tech assists epilepsy diagnosis
PhD researcher David Ahmedt is using motion recognition technology to help neurologists study the brain's behavior during epileptic seizures.Find out more
Advantage: big data
Our researchers have developed an algorithm that can predict where a tennis player will hit the next ball by analysing Australian Open data of thousands of shots by the top male tennis players.Read the article here
Real time flight path prediction
Our researchers have harnessed data analytics to build an algorithm that can predict the trajectory of any object faster and more accurately than existing approaches.Read the article here
Improving airport experiences
Discipline leader Professor Clinton Fookes and his colleagues have designed video analytics software that uses CCTV feeds to help improve passenger flow at airports, as well as spotting potential security risks.
Our discipline makes sense of the world’s data streaming in from cameras, devices, and sensors.
Our expertise in machine learning, computer vision and signal processing allows us to develop systems to automatically interpret the world, its people and their activities from visual and audio sources.
We improve our ability to interact and sense our environment through advanced wireless communications and electromagnetics.
We aim to improve human health through AI, medical imaging and signal processing.
Our discipline brings together a diverse team of experts who deliver world-class education and achieve breakthroughs in research.
Explore our staff profiles to discover the amazing work our researchers are contributing to.
- Senior Lecturer in Electrical Engineering
- Division / Faculty
- Vision and Signal Processing,
School of Electrical Engineering, Computer Science
- Research fields
- Electrical and Electronic Engineering
- Communications Technologies
- Curriculum and Pedagogy