Time series clustering, visualisation and explainability - Applications in Climate Change and Finance

For this project the appropriate time series clustering techniques will be used to find underlying structures in the financial and phenological data. The structures found will then be visualised, with the suitable explainability techniques being used to describe and interpret the time series clustering methods that were utilised.

Dillon Batdorf

RMIT University

Dillon Batdorf is a third-year student at RMIT University, majoring in Applied Mathematics and Statistics. Dillon’s research interests broadly encompass the applications of machine learning and statistical techniques in various domains.

You may be interested in

Sami Salem

Sami Salem

Applicability of Discrete Fourier Transforms in Denoising Images
Joseph Kwong

Joseph Kwong

SO(n)-invariant Einstein metrics
Daniel Claassen

Daniel Claassen

Extreme Events and Critical Fluctuations in Generated Time Series Data
Aaron Alonso Garcia

Aaron Alonso Garcia

A model-based approach for estimating Group A Streptococcus transmission pathway parameters from transmission networks inferred from Whole Genome Sequence data.
Contact Us

We're not around right now. But you can send us an email and we'll get back to you, asap.

Not readable? Change text.