PhD Candidate


Kim Bente (University of Sydney)

Bachelor of Science in Management & Technology
Graduate Certificate in Data Science
Master of Data Science

My research interest is in quantifying and communicating uncertainty within environmental modelling. I am particularly interested in the application of probabilistic machine learning techniques to the polar Earth and Climate Sciences: Currently I am working on Bayesian Optimisation for subsurface inversion of Antarctica’s ice to inform uncertainty-aware decisions about ice core drilling and other climate research efforts, which are critical to understand the past, and predict future climate. Furthermore, I am interested in the discovery of causal driver of the changing climate using Causal Inference methods, and I also wants to explore a human-centred perspective on effectively presenting probabilistic modelling to domain experts.

I have a Bachelor of Science in Management and Technology from the Technical University of Munich, Germany, with a major in chemical engineering. I completed the Graduate Certificate in Data Science (with High Distinction) from the University of Sydney, followed by a Master of Data Science (with High Distinction), also from Sydney. Moreover, I have worked as a Research Associate on an interdisciplinary nutrition and public health project among others, and as a tutor for Algorithms, Data Analysis in the Social Science, and Human-in-the-Loop Data Analytics. Driven by the goal to foster community I am a representative for postgraduate research students at the School of Computer Science and a founding member and Vice President of the Postgraduate Research in Engineering Student Society (PRESS).

Prior to adventuring into academic research, I have gained professional experience in the consumer goods sector, in management consulting and innovation consulting, as well as in customer analytics at a Berlin-based software start-up, which led me towards my passion for everything data. When I am not looking at data, I enjoy hiking, running, or swimming through nature, and looking at maps – my favourite representation of spatial data. When temperatures drop below zero, I change my runners for skis: My experience working as a skiing instructor near melting glaciers motivates me to work on the frontier of Data Science to tackle the climate’s future on thin ice.