Sevvandi Kandanaarachchi

Research Fellow, Department of Econometrics and Business Statistics

Monash University


Hello! Thanks for visiting my site! πŸ‘‹

I am a mathematician working on data science related topics such as anomaly detection, meta-learning and streaming data. I conduct research on theoretical and real-world problems. For example, visualizing anomalies in high dimensions is a very tricky business. How can we reduce dimensions in a way that anomalies are highlighted or brought to the forefront? (For details, see dobin).

I come to statistical learning from a pure mathematics background. My PhD was in mean curvature flow, which lies in the intersection of partial differential equations and differential geometry. I like to bring my geometric intuition to solve data science problems. More details can be found on my CV.


  • Data Science
  • Anomaly Detection
  • Streaming Data
  • Event detection
  • Meta-learning
  • Dimension Reduction


  • Graduate Certificate in Data Mining and Applications, 2015

    Stanford University

  • PhD in Mathematics, 2011

    Monash University

  • MSc Preliminary in Mathematics, 2007

    Monash University

  • BSc Eng. in Computer Science and Engineering, 2002

    University of Moratuwa



Research Fellow

Department of Econometrics and Business Statistics, Monash University

Jan 2018 – Present Clayton, Melbourne

Research Fellow

School of Mathematical Sciences, Monash University

Jan 2016 – Dec 2017 Clayton, Melbourne

Assistant Professor, Mathematics

DigiPen Institute of Technology, Singapore

Aug 2011 – Aug 2015 Singapore

Recent & Upcoming Talks



Event detection and early classification for streaming data - an R package.


Dimension reduction for outlier detection - an R package.

Recent Posts

Using dobin for time series data

The R package dobin can be used as a dimension reduction tool for outlier detection. So, if we have a dataset of \(N\) independent …

Space junk podcast

We humans leave such a lot of junk in space. If you’re interested in space junk, you can listen to two podcasts that I co-conducted …