DrKanishka Ranaweera

Dr Kanishka Ranaweera is an artificial intelligence and machine learning specialist with expertise in privacy-preserving machine learning, federated learning, biomedical AI, and trustworthy model development. His work focuses on enabling secure and efficient model training across decentralised and sensitive data sources, particularly in healthcare and other high-stakes environments.

His research includes the development of utility-enhancing methods for differential privacy, adaptive optimisation techniques for low-data settings, and multi-objective frameworks that balance privacy, fairness, robustness, and predictive performance. He has also contributed to anomaly-resilient federated learning, client clustering, equitable model aggregation, and methods for improving the reliability of distributed machine learning systems.

Kanishka’s broader research portfolio focuses on the application of AI in biomedicine. His work includes analysing kinematic and kinetic data from wearable sensors, developing machine learning methods for objective disease assessment, and creating data-driven measures of neurological disease severity and progression. His research spans artificial intelligence, statistical modelling, generative methods, personalised medicine, and neurological disorder analysis, with an emphasis on developing systems that are robust, interpretable, clinically meaningful, and ethically responsible.

He has extensive experience working with interdisciplinary teams across engineering, clinical research, data science, and software development. His expertise covers the complete machine learning lifecycle, including data preparation, statistical analysis, model development, validation, reproducibility, deployment, and regulatory traceability. Through these collaborations, he works to translate advanced AI research into practical technologies with measurable clinical and societal impact.

Kanishka completed his PhD in Artificial Intelligence at Deakin University as a recipient of the prestigious CSIRO Data61 Scholarship. He previously completed a Bachelor of Engineering (Honours) in Mechatronics and Robotics at Western Sydney University, graduating as the top student in his cohort and receiving the University Medal. He was also awarded the Vice-Chancellor’s Award and received Dean’s Merit recognition for five consecutive years.