Priyanga Dilini Talagala
PhD, Monash University, Australia




 



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Priyanga Dilini Talagala

PhD in Statistics

Monash University, Australia

I am a Senior Lecturer in the Department of Computational Mathematics, University of Moratuwa. I earned my PhD in Statistics from Monash University, Australia, under the supervision of Professor Rob J. Hyndman and Professor Kate Smith-Miles. I am a fellow of OWSD, a programme unit of UNESCO (2021-2022).

I am an Associate Editor for The R Journal. Further, I am a co-founder of R-Ladies Colombo, a local chapter of the R-Ladies Global Organization.

My research focuses on statistical machine learning and data mining, and in particular the development of novel methods and tools for analyzing complex data. I am also strongly committed to developing open source software tools to facilitate reproducible research. You can find some of my projects here. Visit me on twitter, I post mostly about R, Statistics, Data Science and science in nature.

I am an Associate Investigator of the Australian Research Council (ARC) Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS), Australia, 2019 - 2021.

Thiyanga Talagala, PhD in Statistics, Monash University, Australia is my sister.

Interests

  • Computational statistics
  • Statistical machine learning
  • Machine learning interpretability
  • Anomaly detection
  • Time series analysis and forecasting
  • High dimensional data visualization
  • Streaming data mining
  • Responsible AI
  • Applied statistics
  • R programming

Education

  • PhD in Statistics, 2019

    Monash University, Australia

  • BSc (Hons) Special Degree in Statistics, 2013

    University of Sri Jayewardenepura, Sri Lanka

  • Batch first and Professor R A Dayananda Gold Medalist, 2013

Featured Publications




Featured Publications

Anomaly detection in high-dimensional data - in JCGS

This article proposes a framework to detect anomalies in high dimensional data using feature engineering.

Anomaly Detection in Streaming Nonstationary Temporal Data - in JCGS

This article proposes a framework that provides early detection of anomalous series within a large collection of non-stationary streaming time series data.






Recent Publications

Quickly discover relevant content by filtering publications.

COVID-19 and Online Learning Tools

Distance education has a long history. However, COVID-19 has created a new era of distance education. Due to the increasing demand, …

Responsible AI: The talk of the Town

This article discusses the significance of responsible AI for the protection of humanity in an exceedingly unpredictable future.

Anomaly Detection in High Dimensional Data

The algorithm, stray, which is specially designed for high-dimensional data, addresses the limitations of the state-of-art-method, the …











Recent & Upcoming Talks

Anomaly Detection in Image Streams with Explainable AI

OCTAVE Advanced Analytics Symposium, May 20, 2022

Detecting Technical Anomalies in Water-Quality Data From River Networks

Joint Aquatic Sciences Meeting in Grand Rapids, Michigan, May 14-20, 2022

Technical Anomalies in Water-Quality Data From In-Situ Sensors - What, Why, and How?

Anomalies in water quality data due to technical errors from in situ sensors can reduce data quality and have a direct impact on …

Attention Towards Distance Education Tools During COVID-19 Pandemic - Evidence from Google Trends

OWSD 6th General Assembly and International Conference

Anomaly Detection in Spatio-Temporal Tensor Streams

2021 Joint Statistical Meetings











Projects

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CRAN Task View: Anomaly Detection with R

CRAN Task View: Anomaly Detection with R.

oddstream - R package

oddstream {Outlier Detection in Data STREAMs}

oddwater - R package

oddwater{Outlier Detection in Data from WATER-quality sensors}

staplr - R package

A package containing a toolkit for PDF files

stray - R package

stray {Search and TRace AnomalY}

Outreach

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Data Analysis with Python Programming for Beginners

This hands-on workshop aims to equip participants with the fundamentals of programming in R and give them skills needed to apply data …

RETINA

RETINA (REvolutionising monitoring systems and Techniques in the INformation Age) is a research and innovation project funded by the …

R-Ladies Colombo

R-Ladies is a worldwide organization whose mission is to promote diversity in the R community. R-Ladies Colombo chapter is a part of …

PyTips

Data Analysis with Python Programming for Beginners.

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