Nick Pawlowski
Quantitative Researcher
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolNick Pawlowski is a quantitative researcher based in London with 11 years of experience at the intersection of machine learning, medical imaging and large-scale research engineering, currently at G-Research after a senior research role at Microsoft. He holds a PhD from Imperial College London and an MSc in AI from Edinburgh, and has contributed across top labs including Google Health, FAIR, X and Facebook where he combined deep research with production-focused engineering. His open-source work on the DLTK medical imaging toolkit improved core I/O, model save/load and documentation publishing, reflecting a focus on reproducible research and deployment. Nick’s background blends physics-informed problem solving, hands-on DevOps for GPUs and scientific computing, and a track record of transferring models from research prototypes into usable tools.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD), High Performance Embedded and Distributed Systems, Doctor of Philosophy (PhD), High Performance Embedded and Distributed Systems at Imperial College LondonBachelor of Science (BS), Physics, Bachelor of Science (BS), Physics at University of LeedsMaster of Science (MSc), Artificial Intelligence, Distinction, Master of Science (MSc), Artificial Intelligence, Distinction at The University of EdinburghBachelor of Science (BS), Physics, 2.3, Bachelor of Science (BS), Physics, 2.3 at Humboldt-Universität zu BerlinAbitur, Examination subjects: Maths, Physics, German, History and a coursework in Physics, 1,3, Abitur, Examination subjects: Maths, Physics, German, History and a coursework in Physics, 1,3 at Landesgymnasium Sankt Afra, Meißen, Hochbegabtenförderung
English, German, Spanish
Github Skills (11)
machine-learning10
deep-learning10
tensorflow10
python10
medical-image-analysis9
documentation9
faster-rcnn8
mask-rcnn8
image-processing8
devops8
data-science7
Programming languages (6)
Github contributions (5)
DLTK/DLTK
Jun 2017 - Nov 2018
Deep Learning Toolkit for Medical Image Analysis
Role in this project:
ML Engineer & DevOps Engineer
ML Engineer & DevOps EngineerContributions:138 commits, 15 PRs, 98 pushes in 1 year 5 months
Contributions summary:Nick's contributions primarily focused on maintaining and improving the documentation for the project, publishing the Sphinx documentation to GitHub pages and making the project pypi-compatible. They also made improvements to core I/O functionalities, including sliding window processing and augmentation functions, and worked on model-saving and loading routines. Furthermore, the user made changes to example training scripts and improved the handling of exceptions in the reader class.
pythonmedical-imagemedicaltensorflowneuroimaging
pawni/gpuobserver
Jan 2020 - Apr 2021
Contributions:12 commits, 10 pushes, 1 branch in 1 year 3 months
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