Eugene Tan

Eugene Tan is a casual teaching lecturer and PhD student in Multi-Discipline at The University of Western Australia. His primary affiliation is with UWA's research community, focusing on interdisciplinary studies.

Research interests include dynamical systems, machine learning applications in network analysis, and model validation techniques. Notable areas involve network inference using recurrent neural networks, persistent homology for time series analysis, and cognitive dissonance effects in social dynamics.

Recent work explores embedding methods for complex systems, attractor-based change detection, and fault diagnosis algorithms. His contributions bridge theoretical frameworks with practical applications in data science and engineering.

Collaborations span international teams addressing nonlinear dynamics and topological data analysis. No formal awards are listed, though his research shows strong growth in citations and interdisciplinary impact.