Thijs Snelleman
Scientific Programmer and PhD candidate at RWTH Aachen University. Thesis subject is Reproducibility in Artificial Intelligence. Supervised by Professor Holger Hoos (RWTH Aachen & Leiden University) and Professor Odd Erik Gundersen (NTNU, Trondheim).
Scientific Programmer | PhD Candidate
RWTH Aachen University - Aachen, Germany
Working as Scientific Programmer on various internal projects, such as Sparkle, and joint projects such as ConfigSpace.
As PhD Candidate, most of my work is currently focused on the automation of reproducibility of computational research.
Data Scientist
Capgemini - Utrecht, The Netherlands
Data Scientist within the Insights & Data department, member of the Data Science and AI group.
Main project at the National Police, regarding personnel planning and optimisation. Responsible for data analysis, reporting tools and mobile app development for a 60k+ workforce.
M.Sc. Computer Science
Leiden University - Leiden, The Netherlands
Master specialising in Artificial Intelligence (Grade: 8.2/10, Cum Laude). Electives in Natural Language Processing (NLP), Quantum AI, (Geometrical) Deep Learning, Deep Reinforcement Learning. Thesis on automated detection of Coronary Arteries on CCTA scans using Geometrical Deep Learning, in collaboration with the Amsterdam Medical Center (AMC).
Jobs & Internships
AI Summer Intern
Machine Learning Intern
Student Assistant
Data Annotator
Junior Software Developer
Invers - Voorburg, The Netherlands
Junior Software Developer in maintaining and improving a live system focussed on classifying transactional data for mainly business customers (B2B).
B.Sc. Computer Science
Leiden University - Leiden, The Netherlands
Thesis on algorithm comparison on a Dutch card game (“Boerenbridge”), an incomplete information card game, titled “Strategic Gambling in Diminishing Bridge”. Electives in Compiler Construction, Internet Law, Human Computer Interaction, Computer Graphics, and, Data Mining. Average grade: 7.0.