School of Computing

Applied Research in Computer Science (ARCS)

Machine Learning Machine learning is the science of getting computers to act without being explicitly programmed.

- from the Stanford online course on Machine Learning, by Andrew Ng

Machine Learning is a scientific discipline that is concerned with the design and development of algorithms that allow computers to change behavior based on data, such as from sensor data or databases. A major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data.

- from

The Machine Learning Research Group (MLRG) aims to do research in formal aspects of computer science, with the main focus being on Machine Learning.

The groups consists of the following members (in alphabetical order):

Philip Abidoye
Drina du Plessis
Ken Halland
Moses Olaifa
Christian Omlin
Isaac Osunmakinde
Colin Pilkington
Adriaan Pottas
Ian Sanders
Maggie Selepe
Anitta Thomas
Sreedevi Vallabhapurapu
Etienne van der Poel

More information are available under their individual pages on

Active members of this group:

  • Colin Pilkington
  • Etienne van der Poel
  • Ken Halland
  • Wernher Friedrich
  • Anitta Thomas

  • Publications

    This page is not necessarily up to date.


    Chengetanai G.; Osunmakinde, I.O.. (2018)
    Quacs: Routing Data Packets In Ad Hoc Networks On Buffer-constrained Load Balancing Conditions During Emergency Rescue Crisis
    Wireless Personal Communications Journal, Springer International Publishers USA, (ISI journal)
    (99) 3
    pp 1345-1375

    Pilkington, CL. (2018)
    A Playful Approach To Fostering Motivation In A Distance Education Computer Programming Course: Behaviour Change And Student Perceptions
    International Review of Research in Open and Distributed Learning (IRRODL)
    (19) 3
    pp 282-298

    E Zimudzi ; Sanders, I.D.; N Rollings ; C Omlin . (2018)
    Segmenting Mangrove Ecosystems Drone Images Using Slic Superpixels -- Accepted
    Geocarto International

    Alani AY; Osunmakinde, I.O.. (2017)
    Short-term Multiple Forecasting Of Electric Energy Loads For Sustainable Demand Planning In Smart Grids For Smart Homes
    Sustainability journal, Special Issue in Wind Energy, Load and Price Forecasting towards Sustainability, (ISI journal)
    (9) (11)
    pp 1972


    Aruleba, K ; Ewert, S ; Sanders, I.D.; Raborife, M . (2018)
    Preprocessing And Feature Extraction Technique For Hand-drawn Finite Automata Recognition
    pp Paper 48 (9 pages) Electornic proceedings

    Thomas, A; Aurona J. Gerber ; Alta van der Merwe . (2018)
    Ontology-based Spatial Pattern Recognition In Diagrams
    Artificial Intelligence Applications and Innovations
    IFIP AICT 519, Springer
    pp 61-72

    Nuru Jingili ; Sigrid Ewert ; Sanders, I.D.. (2018)
    Measuring Perceptual Similarity Of Syntactically Generated Pictures -- Accepted
    SIMULTECH 2018

    van Staden, WJC; Pilkington, CL. (2018)
    Overcoming The Corporate University And Its Effect On Computing Education
    Southern African Computer Lecturers’ Association (SACLA)
    Cape Town

    Vallabhapurapu, S; Ashwini Rohom; N.B.Chaure; Shengzhi Du; . (2017)
    Bistable Resistive Memory Behavior In Gelatin-cdte Quantum Dot Composite Film
    2nd International Conference on Condensed Matter and Applied Physics
    Bikaner, India
    pp 4

    Coral Featherstone; van der Poel, E. (2015)
    Using Character Valence In Computer Generated Music To Produce Variation Aligned To A Storyline

    Gail Shaw; van der Poel, E. (2015)
    Genetic Algorithms As A Feasible Re-planning Mechanism For Belief-desire-intention Agents