Janith Wanniarachchi

Research

I am a PhD candidate in the Department of Econometrics & Business Statistics at Monash University. I work on explainable AI, data visualisation and interpretable models, and I build open-source R packages along the way.

Projects

kultarr: Anchors, revisited

A pure-R implementation of Anchors that you can debug and visualise. It uses S7 classes, memoised rewards and parallel search, and includes helpers for drawing anchors in high dimensions.

R package · in development

Docs

kumquat: a simpler LIME

A transparent take on LIME for tabular data. It returns the perturbations, predictions and local GLM, so you can audit exactly how an explanation was built.

R package · CRAN

Docs · CRAN

sillysplines: drawn decision boundaries

An interactive widget for sketching a linear-spline decision boundary and downloading the coordinates as a synthetic classification dataset, for teaching and model testing.

R package · htmlwidget

Docs

clamp-maker: sawtooth data in the browser

A Svelte app that runs R in the browser through webR. Sliders set the rotation, overlap, label noise and train/test split of a two-class dataset with a sine-wave boundary, and you can download the result as CSV. It came before sillysplines and is what led to it.

Svelte · webR

Site · GitHub

scatteR: inverse scagnostics

My undergraduate thesis. It generates scatterplots that match target scagnostic measures by placing points with simulated annealing, which gives data for testing visual and ML methods.

R package · CRAN · useR! 2022

Preprint · CRAN · GitHub

Publications & presentations

  • Wanniarachchi, J. (2026). Visual Explanations of XAI Explainers. useR! 2026. Slides & code
  • Wanniarachchi, J. (2023). Seeing the Smoke Before the Fire: Visualising Spatiotemporal Indicators of Bushfires through Counterfactual Explanations of Machine Learning Models. 12th Conference of the Asian Regional Section of the IASC (IASC-ARS), Macquarie University, Sydney. Outstanding Young Researcher / Student Contributed Oral Presentation Award. Slides
  • Wanniarachchi, J. C., & Talagala, T. S. (2022). scatteR: Generating instance space based on scagnostics. arXiv:2209.06682 [stat.CO]. Presented at useR! 2022. doi:10.48550/arXiv.2209.06682 · Talk
  • Karunanayake, V. J., Wanniarachchi, J. C., Karunanayake, P. N. K., & Rajapaksha, U. U. S. (2022). Intelligent System to Verify the Effectiveness of Proposed Teacher Transfers Incorporating Human Factors. 2nd International Conference on Advanced Research in Computing (ICARC), IEEE. doi:10.1109/ICARC54489.2022.9754089

Recognition