- Data Science
- Software/data engineering
- Organising and planning events
- Softball
- Hackathons
My name is Tanja Crijns. I'm 26 years old and currently living in Utrecht, The Netherlands. I have a BSc in AI and a MSc in Data Science from the Radboud University in Nijmegen. I currently work at RTL Netherlands as a Data Scientist, trying to become famous enough within the company so that they allow me to participate on Expeditie Robinson. On this website you will find more information about my interests and projects that I am currently working on.
Interests
Board of study association CognAC 2014-2015
Radboud University, FNWI ©klokgroep
Softball team, Dames 1, Radboud Rangers
Projects
- Hackathons Alliander/BDR Data Science Hackathon 2017: The topic of the hackathon was energy infrastructure maintenance and outages. We combined the available data sources to create a prototype of a tool which they could use to predict power outages that could be caused by maintenance, along with a working demo. We placed first.
- Conversational assistance track TREC For my masters thesis, I studied how BERT could be used in a multi-turn artificial conversational setting. It was great learning experience to join a conference track and to be working with a state-of-the-art NLP technique on a complex problem.
- Legal relevance classification Legal relevance classification of dutch corpora. Near perfect performance in both the supervised and unsupervised approach. Suspicion of data leakage even after thorough examination of variables. The source code and research paper can be found on Github.
- Kaggle competitions I have participated in the Kaggle competition 'The Nature Conservancy Fisheries Monitoring' together with a team. The task was to automatically categorise images that may or may not contain certain types of fish. There are eight categories. We ended the competition in the top 6%. A github repository of our project can be found here.
- Microbleed detection For a medical imaging course, I researched the use of deep learning in the detection of cerebral microbleeds in Traumatic Brain Injury patients. We used a two-step deep learning approach; segmentation and classification. I co-authored the paper that was written on this topic and it was accepted at the SPIE Medical conference in 2017 (session 10).
EnergyHackNL 2018: The topic of the hackathon was smart energy. We worked on detecting unregistered solar panels on satellite images to help predict the load on power infrastructure. We placed first.
Hack Junction 2019: We participated in the ‘Finland’s national park’ challenge of the sustainability track. We created a working prototype of an information appforparkvisitors, pitchslide.
Bertelsmann dataweek hackathon 2020: Together with colleagues, I worked on automatic detection of credits in videos using convolutional neural networks. We placed first.
We also participated in the Kaggle competition 'Planet: Understanding the Amazon from Space'. The objective here was to classify which ground types (forest, cultivation etc.) are present in patches of a satellite image. We approached the problem with deep learning techniques and finished the challenge in the top 12%. A github repository of our project can be found here.