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Group Members


Chris Cleghorn

Stochastic Optimization | Neural Networks | Applications of AI to Radio Astronomy

Research Associates

PhD Candidates

Jonathan Gerrand

Electrical Engineer | Data scientist at Explore-AI | Intelligent systems for Healthcare

Steve James

Transferable abstractions for reinforcement learning

Geethen Singh

Computer vision using satellite data for invasive species management

Beatrice van Eden

PhD candidate at the University of the Witwatersrand. R&D Engineer of the Council for Scientific and Industrial Research (CSIR).

MSc Candidates

Aneesh Chandran

Reinforcement Learning for Anticipatory cobots in an industrial setting

Leroy Dunn

Curriculum Learning in Reinforcement Learning

Chris Fourie

Machine learning, Theoretical / Computational Neuroscience, Healthcare


PhD Students

  • Ofir Marom (2021) - Leveraging Prior Knowledge for Sample Efficient Reinforcement Learning
  • Orhan Can Görür (2020) - Social Cobots: Anticipatory Decision-Making for Collaborative Robots with Extended Human Adaptation
  • Adam Earle (2019) - Spectral Reinforcement Learning
  • Ashley Kleinhans (2019) - Robotic grasping inspired by neuroscience using tools developed for deep learning
  • Ritesh Ajoodha (2018) - Influence modelling and learning between dynamic Bayesian networks using score-based structure learning
  • Ndivhuwo Makondo (2018) - Accelerating robot learning of motor skills with knowledge transfer
  • Pravesh Ranchod (2018) - Skill Discovery from Multiple Related Demonstrators

MSc Students

  • Tlou Bokola (2020) - Knowledge Transfer Using Model-based Deep Reinforcement Learning
  • Roy Eyono (2020) - Learning to Backpropagate
  • Yongama Feni (2020) - Evaluating the Reliability of Quantification Results
  • Shahil Mawjee (2020) - Progressive option extraction with a curriculum of tasks
  • Liron Mizrahi (2020) - Using social context for person re-identification
  • Raesetje Sefala (2020) - Using satellite images and computer vision to study the evolution and effects of spatial apartheid in South Africa
  • Isaac Tarume (2020) - Study of Anomaly Detection in Diverse Populations using Probabilistic Graphical Models
  • Craig Bester (2019) - Multi-Pass Deep Q-Networks for Reinforcement Learning with Parameterised Action Spaces
  • Menzi Mthwecu (2019) - Efficient Search and Tracking for Non-Stationary Targets
  • Benjamin van Niekerk (2019) - Learning Safe Predictive Control with Gaussian Processes
  • Sicelukwanda Zwane (2019) - Using Mixture Density Networks to Model Continuous Action Priors
  • Richard Fisher (2018) - Topology-inspired Probabilistic Path Replanning in Dynamic Environments
  • Jason Perlow (2018) - Raw Material Selection for Object Construction
  • Ntokozo Mabena (2017) - Accelerating Decision Making Under Partial Observability Using Learned Action Priors
  • Michihisa Hiratsuka (2016) - Incremental Learning of Smoothed Dynamic Motion Primitives from Demonstration
  • Steve James (2016) - The Effect of Simulation Bias on Action Selection in Monte Carlo Tree Search
  • Phumlani Khoza (2016) - Electroencephalography brain computer interface using an asynchronous protocol
  • Jeremy Lai Hong (2016) - Adaptive Knowledge Injection for Monte Carlo Tree Search for Imperfect Information Games