Michael Burke


Accepting PhD Students

PhD projects

- Learning dynamics models for model-based robot fluid handling (fun with latte art) - Robot learning from exploratory demonstrations (active medical imaging) - Life-long learning and control with funnels - Robust control of learned latent dynamical systems - Embracing uncertainty in robotics


Research output per year

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Personal profile


Michael Burke is a lecturer specialising in robot learning and control at Monash University, Australia. Prior to this, he was a research associate working on robot learning at the University of Edinburgh, from 2018-2020. Before this, Michael led the Mobile Intelligent Autonomous Systems group at the Council for Scientific and Industrial Research (CSIR), South Africa, where he was responsible for a team of 20 staff and students working in computer vision, machine learning and field robotics and had worked since 2009. He has a PhD in statistical signal processing from the University of Cambridge (2012-2016), a Masters of Science in electronic engineering from Stellenbosch University (2009-2011) and a Bachelors in electronic engineering from the University of Pretoria (2005-2008).

His research interests are in the development of probabilistic machine learning and computer vision tools for robotics applications. Specifically he is interested in bridging robot perception and control, by making use of probabilistic programming and leveraging advances in representation learning. Michael has a broad background in robotics, data science and computer vision research and development in support of industry and government, in applications ranging from agriculture to mining.

Research area keywords

  • Robotics
  • Computer Vision
  • Machine Learning
  • Robot Learning
  • Control systems


Recent external collaboration on country level. Dive into details by clicking on the dots.
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