Erwin Van Thiel
Data Scientist
Netherlands
Summary
👤
Senior🎓
Top SchoolErwin Van Thiel is a pragmatic data scientist with nine years of engineering experience, currently applying ML and data expertise at Rabobank after roles as a data engineer and software engineer via Alten. Trained at Delft University of Technology (BSc and MSc Computer Science) with a minor in electronics for robotics, he blends strong back-end development skills with applied machine learning—evidenced by a production-focused proof-of-concept that automated defect detection on a conveyor belt using transfer learning. Comfortable working independently or in teams, he moves quickly from data collection and labelling to model training and deployment while keeping solutions practical and maintainable. His background across industrial control systems, marketing/acquisition tooling, and financial services gives him a versatile perspective on applying data-driven automation in real-world systems. Colleagues know him for a focused, results-oriented approach and a knack for learning new technologies at pace.
9 years of coding experience
4 years of employment as a software developer
Master of Science in Engineering computer science, Master of Science in Engineering computer science at Delft University of TechnologyVWO Natuur en Techniek, VWO Natuur en Techniek at Stedelijk Dalton Lyceum
Stackoverflow
11reputation
7kreached
0answers
2questions
Github Skills (17)
asymmetric10
loss10
hole-punching9
classification9
bluetooth8
meta-learning8
udp7
social-networking7
kotlin7
visual-studio6
networking6
sdl6
deep-learning5
image-classification5
pytorch5
Programming languages (3)
Github contributions (5)
erwinvanthiel/ASL
Jun 2021 - Jun 2022
Official Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(2020) paper
Contributions:18 PRs, 34 pushes, 8 branches in 1 year
pytorchmulti-label-classificationmulti-labelmulticlass-classificationloss
erwinvanthiel/master-thesis-erwin
May 2021 - Jun 2021
Contributions:14 PRs, 14 pushes, 6 branches in 28 days
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