Curriculum Vitae
PhD candidate, Monash University: explainable AI and data visualisation
janithcwanni@gmail.com · github.com/janithwanni · linkedin.com/in/janith-wanniarachchi · phd.janithwanni.com
Profile
Statistician and R developer. I research how to make machine learning explanations visible and trustworthy, and I build open-source software to do it. I have industry experience in Shiny and R package engineering, I teach at Monash, and I have a track record of community talks and workshops.
Education
2023 – now
PhD, Econometrics and Business Statistics, Monash University, Australia
Thesis: Explaining AI through visual explanations and efficient interpretable models. Supervisors: Dianne Cook, Patricia Menendez, Thiyanga Talagala, Kate Saunders. Australian Government Research Training Program (RTP) Scholarship.
2017 – 2022
BSc (Honours) in Statistics, First Class, University of Sri Jayewardenepura, Sri Lanka
Minors in Computer Science and Mathematics. Statistics GPA 3.88; overall GPA 3.82.
2013
Diploma in Web Engineering, ESOFT Metro Campus
Research projects
Chapter 2
Visual explanations of XAI explainers: geometric representations of LIME, SHAP, counterfactuals and Anchors in the data space.
Chapter 3
Random seeds and the complexity–parsimony trade-off: the seed sensitivity of simple neural networks, with a Shiny teaching tool.
Chapters 4–6
kultarr, kumquat and sillysplines: transparent R implementations of Anchors and LIME, and an interactive generator for synthetic data.
Publications & presentations
2026
Wanniarachchi, J. Visual Explanations of XAI Explainers. useR! 2026.
2023
Wanniarachchi, J. Seeing the Smoke Before the Fire: Visualising Spatiotemporal Indicators of Bushfires through Counterfactual Explanations of Machine Learning Models. 12th IASC-ARS Conference, Macquarie University, Sydney.
2022
Wanniarachchi, J. C., & Talagala, T. S. scatteR: Generating instance space based on scagnostics. arXiv:2209.06682. Presented at useR! 2022.
2022
Karunanayake, V. J., Wanniarachchi, J. C., Karunanayake, P. N. K., & Rajapaksha, U. U. S. Intelligent System to Verify the Effectiveness of Proposed Teacher Transfers Incorporating Human Factors. ICARC 2022, IEEE. doi:10.1109/ICARC54489.2022.9754089
Software
Author
kumquat (CRAN): transparent LIME · scatteR (CRAN): scagnostics-driven data generation · kultarr: Anchors in pure R · sillysplines: interactive spline data generator
Contributor
DSjobtracker, nic and tsdataleaks (all on CRAN): data curation, colour palettes, and Rcpp performance work
Experience
2023 – 2024
Teaching Associate, Monash University
Tutorials for ETC5523 Communicating with Data (Shiny, R packages, storytelling with visualisation) and ETC5512 Wild-Caught Data (collecting and wrangling tabular and geospatial data).
2022 – 2023
R/Shiny Developer, Appsilon
Built Shiny dashboards and provided software engineering support for R package development for life-sciences clients.
2021 – 2022
Contractor Consultant, labml.ai
Analysed online user segments and feature usage, and recorded research paper explainers (e.g. DeepMind’s RETRO).
2020 – 2021
Trainee Data Analyst, Trabeya
Built the deduplication component of an automated data-cleaning product and a session-based recommender served through a real-time microservices backend.
2021
Consultant Data Analyst, CreativeHub
Built a hypothesis-testing framework and dashboards for Facebook ad campaigns.
2019
Contractor Consultant, Intellimorph
Built anomaly detection for robotic process automation and a computer vision system for a robotic hand.
2021
Consultant, Statistical Consultancy Service, University of Sri Jayewardenepura
Curated and cleaned the 2021 DSjobtracker data for CRAN.
Awards
2023
United Nations Datathon: 2nd place globally and 1st in the Oceania region (team of five; solar-farm siting web app).
2023
Outstanding Young Researcher / Student Contributed Oral Presentation Award, IASC-ARS 2023.
2022
SLAAS Physical Science Award in Statistics, Sri Lanka Association for the Advancement of Science, for the best BSc Statistics (Hons) research.
2022
useR! 2022 diversity scholarship; top 10 finalist, Octave Advanced Analytics Symposium; nominee for the Most Venerable Sri Sumangala Gold Medal, University of Sri Jayewardenepura.
2017 – 2020
1st runner-up at hackStat 2.0 (2019) and the SLIIT Codefest Datathon (2019); finalist at Data Storm 2.0 (2020) and the Dialog Datathon; honourable mention at the Asia-Pacific Informatics Olympiad (2017); IEEEXtreme 12.0 global rank 487.
Selected talks
2019 – 2026
useR! 2026 · IASC-ARS 2023 · useR! 2022 · Abuja useR Group (2022) · EDEX Expo (2022) · R-Ladies Colombo (2021) · Fundamentals of Data Visualisation and Tableau workshops (2021) · GDG ML Bootcamp (2019) · TensorFlow All Around (2019). Full list at janithwanni.netlify.app/talks.
Leadership & service
2022
Session chair, useR! 2022 (Inference Methods).
2020 – 2021
President, Statistics Society, University of Sri Jayewardenepura. Founded the Pearl Viz data visualisation competition and ran the “Ask the Experts” alumni panel (200+ students) and the Outliers student writing programme.
2019
Head, TensorFlow User Group Sri Lanka. Organised TensorFlow All Around 2019.
Skills
Languages
R (Shiny, package development, S7, Rcpp, tidyverse), Python (PyTorch, TensorFlow), JavaScript/Svelte, SQL, C++
Tools
Quarto, Git, Azure SQL, Google Cloud, Tableau, Power BI
English
IELTS overall 8.0 (Listening 9.0, Reading 9.0)