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Research area(s)

Research interests include:

  • Data-Driven AI
  • Machine Learning (ML)
  • Artificial Intelligence (Al)
  • Deep Learning (DL)
  • Intelligent Data Analysis (IDA)
  • Time Series Analysis
  • Predictive Modeling
  • Sequential Clustering

Research Interests

My current research focuses primarily on modelling academic performance. This typically involves analyzing and predicting the probabilities of unknown events using probabilistic models (Bayesian Networks). I am also interested in clustering Time-Series trajectories to profile and detect students' engagement types and learning patterns.

Research project(s) and grant(s)

Brunel Student Assessment and Retention Project (STARS Project).