THI HAI ANH LUYEN
Clustering Time Series Using Spectral Density–Based Distances
This project investigates how spectral density–based distances can improve time series clustering compared with traditional time-domain approaches. The research focuses on understanding the mathematics of spectral distances, analysing how they capture structural differences such as seasonality and noise, and evaluating their performance against Euclidean and correlation distances. Small experiments in R using TSclust and dtw will be conducted to compare clustering results. A key research question is whether weighting frequency bands can enhance the interpretability and validity of clustering outcomes.
THI HAI ANH LUYEN
Western Sydney University
Luyen Thi Hai Anh is a second-year undergraduate student at Western Sydney University, majoring in Data Science. She is passionate about transforming data into meaningful insights that drive innovation and support real-world decision-making. Her studies have strengthened her interest in data analysis, artificial intelligence, and their applications across different industries.
Hai Anh is also a member of the university’s RAM Robotics team, where she enjoys applying data-driven approaches to technology projects. She looks forward to representing Western Sydney University in Korea in 2026, where she hopes to learn from international perspectives and further explore the connection between data science and innovation.
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