Martijn Gösgens

PhD Candidate at Eindhoven University of Technology

Research

Link to my Google Scholar profile.

An interactive visualization of the Louvain algorithm for community detection.

Community detection

My research focuses on detecting communities in complex networks. Communities are groups of nodes that are better connected internally than externally. Such communities could, for example, correspond to groups of friends on social media or fields of study in citation networks. There are many heuristic algorithms for community detection, but there is limited understanding about which algorithm works well on what network. The most widely-used community detection method is modularity maximization. In this paper, we prove that this method is equivalent to minimizing an angular distance in a hyperspherical geometry. In another paper, we prove that several other community detection methods have the same hyperspherical structure.

Validating validation measures

For many machine learning tasks, there exist many measures to quantify the similarity between two outcomes. These measures are used to validate the performance of a machine learning algorithm by measuring the similarity between the outcome of the algorithm and the desired ('true') outcome. However, there are many of these validation measures, making it difficult to decide which one to use. This choice is especially important since many of these validation measures have inherent biases towards certain outcomes, which may lead to an unfair or suboptimal algorithm being chosen in practice.

For the machine learning tasks of clustering and classification, we mathematically analyzed the most popular validation measures, which led to recommendations about which measure to use in what setting. This resulted in two papers that were published at ICML2021 and NeurIPS2021, regarding the clustering and classification task respectively.

Epidemiological modeling for COVID-19

During the COVID-19 pandemic, we modeled the effect of mobility in the spread of the infections. This led to this publication in JRSI. An interview about this project can be found in the Cursor and a blog about this project (in Dutch) can be found on NEMO kennislink

Experience

Eindhoven University of Technology

PhD Candidate
2020 - Now

My PhD project focuses on community detection in complex networks. This project is supervised by Nelly Litvak and Remco van der Hofstad.

For the KNAW (Dutch Royal Acadamy) and NEMO Kennislink, I write blogs as one of their Faces of Science. The blogs (in Dutch) are aimed at giving a glimpse into the life and work of young scientists. My profile can be found here.

For the Network Pages, a project by the Networks Center, I develop interactive visualizations that help explain network theory in a way that can be understood by non-mathematicians. An example of such a visualization is given below, taken from this blog about bottleneck detection algorithms.

Eindhoven University of Technology

Student Assistant

As a student assistent, I assisted lecturers with various teaching tasks such as supervising student projects and grading assignments.

2015 - 2020

ViNotion

Software Engineer
2018 - 2020

ViNotion is a specialist in the field of automated video content analysis that uses image recognition to analyze traffic. For ViNotion I used a game engine to generate synthetic datasets with ground truth. This data can be used to validate the performance of the products and to experiment with training on synthetic data. This video demonstrates the tool that I built.

Wolfpack

Software Developer
Projects:
  • MedApp: an iOS app to assist patients in taking their medicines. Among others, the app notifies patients when to take their medicines and allows them to order new medicines directly from their pharmacy.
  • ISAAC’s Project Time Management system: a web application that allows employees to log the hours that they have worked and provides clients and project managers insight in the progress of their projects.

2016 - 2017

AthenaStudies

Tutor

For AthenaStudies, I gave exam trainings to help a group of first year Industrial Engineering students prepare for their mathematics resit.

2015

Education

Eindhoven University of Technology

MSc Industrial and Applied Mathematics (Cum laude)

With a specialization in Statistics, Probability and Operations Research. During this master, I did a 3-month internship at Yandex and MIPT in Moscow.

2018 - 2020

Eindhoven University of Technology

BSc Applied Mathematics (Cum laude)
2014 - 2018

Eindhoven University of Technology

BSc Software Science (Cum laude)
2014 - 2018

Software Skills

Interests

Music (Bass guitar, guitar and keyboard)

Bouldering

Programming

I also enjoy programming and software development. An example of one of my hobby projects is NetSweeper, a network-based variant of Minesweeper. The game is described in this blog for the NetworkPages and it can be played here.