Currently completing my Master's degree in Computer Science at Aarhus University. I am quite passionate about data science and math, and so I have chosen to work with data in particular. I am also currently working on a research project with a few friends involving Knowledge Graphs. Between my studies, I like to do volunteer work in (all of the) student associations. I am the former editor (out of 2) of a student magazine, a former mentor and tutor, current treasurer of the Computer Science student association, as well as the current Vicechair of TÅGEKAMMERET. I also like to play with all things Linux.
SciPaWiz: A Tool For Explorative Visualization of Scientific Citation Networksgithub.com/KristofferStrube/SciPaWiz
TThe project uses the DBLP and OpenCitations APIs to construct a visual representation of how scientific papers in the field of Computer Science cite each other.
Fueled by our love of graphs, we created a data visualization tool for citations in scientific papers. Because research papers have a lot of citations, this means that naive graph plots are unwieldly. Visualizing a non-trivial amount of papers in a single plot often results in a huge pile of spaghetti. We used a number of tricks and heuristics in order to deal with the problem of scale of graph plots. The tool is interactive, and allows a person to explore the scientific literature relative to some origin paper.
Volunteer work (only from 2017+)
UNDER CONSTRUCTION STILL
BSc Computer Science
2017 - 2020
Computer Science started at Aarhus University in 1968 as a part of the Department of Mathematical Sciences. In the period 1993–1998, Computer Science went through a rapid growth increasing the total staff from 80 to 160 people – primarily due to a dramatic increase in the amount of external funding. An independent Department of Computer Science was created in January 1998. Over the next 5–6 years, the department gradually moved to new buildings as a part of the university’s plan to concentrate the ITC activities in the IT City Katrinebjerg. There is a close and fruitful collaboration with many other organisations at Katrinebjerg.
I worked with Knowledge Graphs during my bachelor project, investigating if the PageRank
algorithm is a suitable predictor of user behaviour on Knowledge Graphs. During the project,
we also explored if semantic data could improve the ability of the algorithm to predict user
We found that overall, the PageRank algorithm does not have significant predictive power of user behaviour, and our models for improving the algorithm with semantic information did not alter this.
MSc Computer Science
2020 - 2022
For my Master's degree, I am very much focused on Data Science. I am currently working on a
research project involving (surprise!) Knowledge Graphs.
GLIMPSE, or Graph-based Learning of Personal Summaries involves computing personal summaries of massive Knowledge Graphs. These summaries attempt to "predict" which queries a user may have for the Knowledge Graph in the future, and will compute a personalized summary which can be stashed on a user's local device in order to speed up queries, or even allow for queries to be answered offline.
So far, computing these summaries is expensive, and as time goes on, they get more and more out of date. Our project explores if these summaries can be computed dynamically by formulating the problem of choosing which parts of the graph to include in the summary as a multi-armed bandit problem. Specifically, we are interested in actually implementing the multi-armed bandit algorithms to explore how good they are at solving the problem, hopefully helping the theoretical researchers.