Research Interests

  • Data Science / Data Mining / Machine Learning on health-related data, particularly Nutrition and Physical activity data

    interest to move into environmental research
  • Human Computer Interaction (HCI)
  • Data Visualisation
  • Uncertainty, explainable and probabilistic models, communicating uncertainty
  • Process Mining


Headshot of Kim Bente

My name is Kim Bente and I am a Research Associate at the School of Computer Science, University of Sydney. My research interests are centred around using Data Science techniques on health related data. I am part of the multi-disciplinary Human-centered technology research cluster led by my supervisor, Professor Judy Kay. My current research is interdisciplinary, applying an array of Data Science techniques like classification models, association rules, and data visualisation, to data from a Public Health Nutrition Study, which used a smartphone app to record participants' diet. I have also worked on educational data mining and criminology data, and I have a strong interest to expand to environmental topics in the future.

I have completed the Master of Data Science [with high distinction] from the University of Sydney in 2020 and I hold a Bachelor of Science from the Technical University Munich, in Management & Technology, specialising in Chemical Engineering.

I am very excited about the prospect to do start a PhD, and I am currently seeking funding opportunities.

Please contact me through


  • Master of Data Science, The University of Sydney, Australia

    completed with High Distinction in 2020

    Final research project (Capstone) 'New Perspectives on the Validation of a Mobile App for Dietary Assessment using Data Mining', supervised by Professor Judy Kay

    Faculty of Engineering Summer Research Program Scholarship 2019/2020 for the project 'Data mining of dietary patterns', supervised by Prof Judy Kay, A/Prof Irena Koprinska and A/Prof Kalina Yacef
  • Graduate Certificate in Data Science, The University of Sydney, Australia

    completed with High Distinction in 2019
  • Bachelor of Science in Management & Technology, Technical University of Munich, Germany

    Specialisation in Chemical Engineering

    Bachelor's Thesis about 'Knowledge Management in a Dynamic Organisation'


  • Tutor for Data Analysis in the Social Sciences [DATA5207], United States Study Centre

    Intensive February 2021, postgraduate level tutoring
  • Tutor for Algorithms [COMP9007], School of Computer Science

    Semester 2 2019, postgraduate level tutoring
  • Course analytics for Human-in-the-Loop Data Analytics [DATA3406], School of Computer Science

    Educational data analytics, student performance feedback with SRES, development of a computer-based marking program for Semester 2 2020

Professional Experience

  • Customer Analytics and Customer Relationship Management at FOURSOURCE, a tech start-up in apparel sourcing, Berlin, Germany
  • Innovation Consulting and Ideation, Junior Innovation consultant, HYVE, Munich, Germany
  • Management Consulting, media sector, working student, goetzpartners advisory, Munich, Germany
  • Research & Development (R&D) and International Marketing, internships, consumer goods sector, Schwarzkopf (Henkel), Hamburg, Germany
  • Product development and product management, internship, consumer goods sector, Kneipp, Würzburg, Germany

Outside of research...

  • Running, Cycling, Tennis, Swimming, Skiing
  • Designing and sewing timeless garments and other textile creations
  • Cooking healthy food, travelling, exploring art

Daily Data Dose

The Daily Data Dose [DDD] is a compilation of my favourite data-related resources, both informative & entertaining. My shortlist includes podcasts, websites, talks and other useful things that I came across. Most of these I have recommended to a plethora of data-enthusiasts, so it was time to put a list on the web. I thank everyone who has introduced me to any of these gems. Links are included below.

  • The Dataframed podcast

    This is my favourite Data Science podcasts! I have listened to every of the 60 episodes at least once, soaking up insights from industry to academia. I can't recommend this enough, and if you know me I will have likely already recommended it to you.

  • 'AI for Earth' projects by Microsoft

    I learnt about some of the projects from 'AI for Earth' at a very inspiring talk by Jennifer Marsman at the Microsoft reactor in Sydney. I was very fascinated by the creative use of AI, especially by the World Mosquito Program and the Whalebook. I recommend checking out the projects.

  • Process Mining Coursera course by Professor Wil van der Aalst

    I took this course on Process Mining which is not only interesting from an algorithmic point of view but very relevant for any temporal or procedural data set. Great course!

  • "Environment Variables: how software impacts climate change" - Merrin Macleod (PyCon AU 2019)

    This is an outstanding talk which was recommended to me by a colleague (Thanks Ben!). If you care about the environment and you work in tech, you will surely learn something new here.

  • The Pudding

    The Pudding is website which publishes visual essays about societal and cultural topics. They are pushing the boundaries of data journalism and therefore always worth a digital visit.

  • Gapminder

    Gapminder is a great organisation that promotes a more fact-based worldview. They also have an extensive collection of open access data sets. Furthermore, I highly recommend reading the book 'Factfulness' by Hans Rosling.

  • Information is Beautiful

    A collection of informative and visually appealing data visualisations.

  • Google dataset search tool

    A search engine for data sets. A very useful tool to find openly available data sets.

  • Data Science by John D. Kelleher and Brendan Tierney

    I recommend this book to family and friends who want to understand what I do, but I also like going back to this pocket book by MIT Press to reset my own perspective for the big picture.

  • Papers with code

    Professor Caren Han's NLP course [COMP5046] introduced me to this site, which is a great resource to stay on top of the latest ML research in different fields.

  • Datasaurus, the new Anscombe's quartet

    An updated and more creative version of the Anscombe's quartet, including animated visualisations. This demonstrates once again that summary statistics are not enough to describe data.

  • Spurious correlations blog by Tyler Vigen

    A good reminder that correlation ≠ causation.

  • The True size of ...

    This is a fun web tool to understand the distortion of the size of countries, as they are displayed on the world map.


built by Kim Bente