I am a student with experience both in backend and frontend development.
I have a Master's degree in Computer Science: Artificial Intelligence. Currently I am enrolled in Master of Information Management. Most of my job experiences are in backend development, however I would like to sharpen my frontend development skills.
Hackathons are my true passion as I enjoy being challenged and getting the opportunity to use the skills I have learned and develop them even further.
I am known as a social person who learns quickly and works in a solution-oriented fashion.
I graduated with a bachelor's degree in Informatics at the university of Leuven. I chose Science as my minor during this 3 year degree.
I graduated with a master's degree in Civil Engineering: Computer Science with a major in Artificial Intelligence. My electives have mainly been in frontend development.
I am currently enrolled in the Master of Information Management
Would you like to know more or just discuss something?
I am always happy to land a new internship or summer job and learn a lot of new stuff.
Helped building an API using the Python Django framework. Mainly worked on the backend in the beginning. After a while my main task was to increase the coverage of the unit tests for another API.
Student Web Developer
Student consultant for Oh’Green. Oh’Green is a green experience store located in Belgium. They have 11 stores but have lost the overview of their assortment. Mainly doing big data analytics and helping them harmonize their product assortment over all their stores in order to increase customer satisfaction. My main task was to automate the harmonization process.
Student Consultant
TalkToC is a company that tries to create personalized e-learning by gathering statistics from their users and using AI to predict the best triggers to send. I have helped them develop their backend using the Python Django framework.
Backend Development
For 6 weeks I was able to help the Deepfield team of Nokia building a Python library that connects to DPDK via Cython. DPDK is a C framework that can send packets at a very high speed by by-passing the Linux kernel. By creating a Python API it can be easily integrated with the rest of Deepfield's code base.
Software Development
Academics for Technology is a student organization offering workshops and events for students at KULeuven. During the 2020-2021 academic year I had the honor to maintain and develop their IT infrastructure, this includes setting up a contact database and redesign their website from the bottom up.
IT Manager
During the second semester of the 2020-2021 academic year I will be a student assistant for the course “Methodiek van de informatica”, giving the exercise sessions to first bachelor’s students.
Student Assistant
At OSOC I had the chance to build a REST API for the Flanders Marine Institute (VLIZ) which allows users to parse a citation and get the different parts in JSON format. I also build a user interface for the web.
Software Development
Spottr is a KU Leuven spin off company which reduces energy waste through AI-assisted utility monitoring. I was responsible for building their website. For this I used React and Flask.
Website Development
I have worked on dozens of projects so I have picked only the latest for you.
During one of my project courses at university I built a food recommendation application tailor-made for students using the Flutter framework. There is a possibility to create a meal plan and opt for easy-to-make meals.
This application was made in a team of 5 students. With this application we researched possible solutions to the cold-start problem of recommender systems.
For my thesis I built a book recommendation application using the Meteor framework. This book recommendation application uses content-based filtering to recommended new books to users.
Mainstream recommender systems such as Netflix and Amazon provide very little explanation as to why a recommendation has been made to a particular user. In my research I researched whether visual explanations showing the decision process of the recommender system to recommend new books increases the user satisfaction.
During one of my project courses at university I built a recommender system for movies based on the movielens dataset.
One of the main issues with recommender systems is the cold start problem. In this project I investigated possible Positive Unlabeled (PU) Learning algorithms to solve this problem together with my project partner. We did this by converting the dataset into a PU Learning problem. After which we trained a model using two-step techniques and class prior incorporation methods.
During one of my project courses at university I had the opportunity to exploit memory vulnerabilities in C programs.
The goal was to be able to execute the /bin/sh command which runs the system shell. The attacks consisted of buffer overflows, data-only vulnerabilities, stack-based buffer overflow, return-to-libc and format string vulnerabilities.
During one of my project courses at university I had the opportunity to built a multi-agent system in which a swarm of 1000 robots is able to communicate with each other and form predefined shapes.
When two robots get near each other they can communicate, a robot that is already at its final destination can inform another robot which way he should continue. Four robots are used as to initialize the coordinates of the grid.
During one of my project courses at university I had the opportunity to built an agent-based algorithm which was able to learn Kuhn and Leduc poker which are simplified poker versions.
Two different algorithms based on regret minimization already existed in the literature, namely outcome and external sampling. I proposed and researched a hybrid system utilizing these two methods.
