As a postdoctoral research fellow at the Australian Institute for Machine Learning, I will be leveraging machine learning techniques to determine the probability distribution of collaboratively interacting entities in complex, noise-laden datasets. Previously, during my postdoctoral research at CSIRO, I utilized Graph Neural Networks (GNNs) to predict relationships between species and chemicals, tackling the challenges posed by diverse and varying experimental conditions. During my PhD at the Queensland University of Technology, Brisbane, I developed effective unsupervised representation learning methods for time series and trajectory data. This diverse experience equips me with a robust foundation to address diverse, complex, data-intensive scientific problems with innovative solutions.