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

Kate Zhang

Kate Zhang

Long-Term Behaviour of Ranking-Based Polya Urn Models
Liam Wood-Baker

Liam Wood-Baker

Properties of Random Walks and their applications to Mathematical Physics
Michael Kaminski

Michael Kaminski

Data Assimilation for Korteweg-De Vries Equations
Muhammad Haris Rao

Muhammad Haris Rao

The Representation Theory of Hecke Algebras Through the Knizhnik-Zamolodchikov Functor
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.