
Thomas Van Dongen
Data Scientist

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About me
Head of AI Engineering @ Springer Nature | The Minish Lab
Education

Praedinius Gymnasium
2009 - 2015
Rijksuniversiteit Groningen
2015 - 2018Bachelor's degree Information ScienceActivities and Societies: A.S.V. Dizkartes

University of Groningen
2018 - 2020Master's degree Artificial IntelligenceGraduated cum laude (9.5 thesis, 8.4 average grade).Thesis title: "Quality Prediction of Scientific Documents Using Textual and Visual Content".

Rijksuniversiteit Groningen
2017 - 2018Pre-master Artificial IntelligenceCompleted all pre-master courses during my Information Science bachelor.

Rijksuniversiteit Groningen
2016 - 2017Minor Artificial Intelligence
Experience

IChoice4U BV
Dec 2017 - May 2019Data ScientistWorked as a data scientist/research assistant on data from Pscribe.

Gronalytica
Jun 2019 - May 2021Co-founderDeveloped a platform for automatic grading of pharmaceutical exams at pharmagrader.com. Funded by SNN.

Slimmer AI
May 2021 - Oct 2023Machine Learning EngineerWorked as a machine learning engineer and tech lead of the recommenders team, developing ML products in the scientific domain.

Springer Nature
Oct 2023 - nowLeading a team of engineers to build AI-driven solutions that improve scientific publishing.For over 180 years Springer Nature has been advancing discovery by providing the best possible service to the whole research community. We help researchers uncover new ideas, make sure all the research we publish is significant, robust and stands up to objective scrutiny, that it reaches all relevant audiences in the best possible format, and can be discovered, accessed, used, re-used and shared. The Slimmer AI science division was acquired by Springer Nature after successfully working on ML products together for a number of years. I continued my role as technical lead of the recommenders team.
Head of AI Engineering
Dec 2024 - nowSenior Machine Learning Engineer
Oct 2023 - Dec 2024

The Minish Lab
Sept 2024 - nowCo-founderDeveloping open source ML software with a focus on efficiency and eco-friendly models. Our GitHub org: https://github.com/MinishLab.We are currently working on the following open source projects:- Model2Vec: Fast State-of-the-Art Static Embeddings- Vicinity: Lightweight Nearest Neighbors with Flexible Backends- SemHash: Fast Semantic Text Deduplication- Potion models: State-of-the-art Static Embedding Models
Licenses & Certifications
- View certificate

R Programming
CourseraNov 2016 - View certificate

Neural Networks and Deep Learning
CourseraAug 2017
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