Hi, I'm Jeroen Offerijns

I'm a software engineer. I like teaching machines to learn, creating new products using technologies that explore the edges of what's possible, and designing new experiences.

Work Experience
Gigster
2018 -
Software Engineer (Network)
react
node.js
typescript
graphql
Magnet.me
2016 - 2017
ML Engineering intern
scala
spark
Faqta
2015 - 2016
Software Engineer (freelance)
angular
node.js
Research
Better Distractions: Transformer-based Distractor Generation and Multiple Choice Question Filtering
For the field of education, being able to generate semantically correct and educationally relevant multiple choice questions (MCQs) could have a large impact. While question generation itself is an active research topic, generating distractors (the incorrect multiple choice options) receives much less attention. A missed opportunity, since there is still a lot of room for improvement in this area. In this work, we train a GPT-2 language model to generate three distractors for each question, using the RACE dataset. Our model outperforms earlier work on distractor generation (DG) and achieves state-of-the-art performance. Next, we train a BERT language model to answer MCQs, and use this model to filter only corectly answered question. This improves not only our own results, but can also be used to enhance other question generation models.
DeepMorpheus: Morphological Tagger for Ancient Greek and Latin
For classical languages such as Latin and Ancient greek, determining morphology (gender, word type, etc) is of particular importance. However, most automated tools for this still rely on old machine learning techniques, rather than employing modern deep learning based models. We decided to create a BiLSTM based model, using the Perseus dataset for both languages. We trained a model which employed both word-level and character-level features, creating its own embeddings while training, outputting 9 different tags for each word. Our model greatly improves over previous works and achieves state-of-the-art results, with an overall accuracy over all tags of 96%, and a word type accuracy of 79%, for Ancient Greek.
Creative Coding Projects
python
arduino
minimax
Shallow Green
We built a checkers playing robot, challenging people around the robot to play against it and taunting them when they were losing. We built a robot arm with Arduino components, which could move checker pieces using a magnet. The board was detected using a camera on top of the board, running computer vision to determine where all the pieces were. We used a minimax based game AI to determine the next moves, which was very hard but not impossible to beat. And while playing, a microphone was used to talk to the human opponent, giving you instructions, telling you when you made a bad move, and so on.
Chatting with an Alien
A conversational AI, based on GPT-2, with the personality of an alien from Mars.
gpt2
python
Musings Over Port 23
A small Telnet server which disrupts the computer which is in the middle of some activity.
node.js
telnet
Other Projects
42 Education
2015 - 2017
Created a platform for educational games.
scala
akka
typescript
Transvise
2013 - 2014
Developed a MOOC platform for higher education.
ruby on rails
Net-Les
2012 - 2013
Worked an online tutoring platform for high school students.
django
Web Assay
2010 - 2012
Created a web application that scans and analyses other websites.
php