Alexander Kensert
Postdoctoral Researcher at UGent
Breda, North Brabant, Netherlands
Summary
👤
Senior🎓
Top SchoolAlexander Kensert is a postdoctoral researcher and Python-based machine learning engineer with eight years of experience applying ML to biological and chemical problems across leading Belgian research institutions. He holds dual PhD training in engineering and pharmaceutical sciences and a master's in molecular biology, blending wet-lab domain knowledge with strong computational skills. At VIB-UGent/UGent and previously KU Leuven and VUB, he has driven interdisciplinary projects that translate complex experimental data into reproducible models and insights. Beyond research, he contributes technical documentation to the Keras project, demonstrating an ability to explain deep-learning concepts clearly to the broader community. Based in Breda, he combines academic rigor with practical software practices, making him effective at both prototyping novel methods and producing production-ready analysis pipelines.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Pharmaceutical Sciences, Doctor of Philosophy - PhD, Pharmaceutical Sciences at KU LeuvenMaster's degree, Molecular Biology, Master's degree, Molecular Biology at Uppsala universitetDoctor of Philosophy - PhD, ENGINEERING, Doctor of Philosophy - PhD, ENGINEERING at Vrije Universiteit Brussel
Stackoverflow
294reputation
10kreached
21answers
0questions
Github Skills (13)
keras10
tensorflow10
documentation10
machine-learning9
deep-learning8
jupyter-notebook8
python8
neural-network6
pandas6
wordlist6
lstm6
bruteforce6
combinations6
Programming languages (3)
Github contributions (5)
keras-team/keras-io
Jul 2021 - Dec 2021
Keras documentation, hosted live at keras.io
Role in this project:
Technical Writer
Technical WriterContributions:17 reviews, 6 commits, 10 PRs in 6 months
Contributions summary:Alexander's commits primarily focus on creating and updating Keras documentation. Their contributions include adding tutorials, revising existing content, and incorporating feedback from reviewers. The user has demonstrated a strong understanding of the Keras framework and effectively communicates technical concepts. They are responsible for the generation and modification of documentation files.
keras
akensert/deep-learning-peak-detection
Oct 2021 - Mar 2022
Implementation of a deep learning model for peak detection in chromatograms.
Contributions:29 commits, 2 pushes in 5 months
deep-learningpeak-detection
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