Braden is a PhD student in Theme 2. He describes himself as a proud mathematician with experience in complex systems and machine learning. He is also skilled in data analysis, communication and tutoring.

Braden completed his degree in applied mathematics with first class honours at the University of Western Australia. His thesis looked at ways of applying reservoir computing (a mix of machine learning and dynamical systems) techniques to time-series diagnosis, with an application to cavitation detection from pump vibration data.

Braden is continuing this research under the supervision of Dr Debora Correa, Prof. Michael Small and Dr Ayham Zaitouny from the University of Western Australia. His work remains on time series analysis with machine learning with a particular focus on reservoir computing, a field of study now known as reservoir time series analysis. This work has led him to look at problems such as time series classification and change point detection, generalizations of real-world problems such as early fault detection and fault mode classification.