Theme 01
AI for personalised learning
Knowledge tracing: estimating what a learner has mastered, attempt by attempt, and reporting how uncertain that estimate is. The estimate is the model's claim about a person, so it is always shown with its band.
Publications
- EIKTAIED, 2025
- Privacy-Preserving Synthetic Data GenerationEC-TEL, 2018
- IKTAAAI, 2022code
- BKT-LSTMArxiv, 2021code
- DSCMNPAKDD, 2019code
- DKT-DSCICDM, 2018code
- KTICDM, 2018
- Q-matrix ReinmentEC-TEL, 2016
- Uni Library Rec. Syst.e-Learning, 2013
Theme 02
Interpretable explanation of tabular models
Bayesian networks and Markov blankets: identifying the smallest set of variables that renders a target conditionally independent of everything else, so an explanation names variables rather than gesturing at importance scores.
Theme 03
Visual generative modeling
Learning what makes an image or video plausible well enough to generate new ones, not just classify or detect what's already there. A model that can generate a scene has learned something about its structure, so generation doubles as a test of whether a system understands what it sees.