Anton Schwaighofer
Machine Learning Engineer at Microsoft Research
Cambridge, England, United Kingdom
Summary
🤩
RockstarAnton Schwaighofer is a Machine Learning Engineer and team lead with 11 years of experience, specializing in AI for medical imaging and grounded in a PhD in machine learning and a computer science degree. He blends deep learning and Bayesian methods with solid engineering practices to deliver reliable, maintainable production systems using Python, .NET (F#, C#), PyTorch and the Azure stack. Anton has a track record across domains from computational chemistry to online advertising, and contributes to major open-source projects such as Microsoft’s InnerEye and CNTK—improving dataset pipelines, PyTorch upgrades, and image evaluation APIs. He focuses on practical improvements that accelerate experiments and deployment (e.g., optimizing dataset preparation and fixing Hyperdrive tagging across runs). Based in Cambridge, UK, he pairs research-grade ML expertise with hands-on cloud and systems engineering to move models from prototype to scalable clinical workflows.
11 years of coding experience
German, English, Spanish
Stackoverflow
3,149reputation
504kreached
74answers
5questions
Github Skills (20)
pytorch10
c-language10
python10
machine-learning10
cntk10
azure-machine-learning10
deeplearning-ai10
deep-learning10
medical-imaging10
cprogramming-language10
csharp9
dotnet-core9
deep-neural-networks9
cplus9
cpp9
Programming languages (10)
Github contributions (5)
microsoft/InnerEye-DeepLearning
Jul 2020 - Aug 2022
Medical Imaging Deep Learning library to train and deploy 3D segmentation models on Azure Machine Learning
Role in this project:
ML Engineer
ML EngineerContributions:3 releases, 605 reviews, 304 commits in 2 years
Contributions summary:Anton's contributions primarily involve modifying the InnerEye Deep Learning library for medical imaging. They made changes to support Linux-style paths, optimized dataset preparation time, and added hooks for customized dataset statistics, indicating a focus on improving the library's functionality and efficiency for deep learning tasks. Furthermore, the user addressed hyperdrive run tag issues by correctly copying them from parent runs, demonstrating an understanding of AzureML's hyperparameter tuning workflows. They also upgraded PyTorch to version 1.6 and refactored LR schedulers.
deep-learningmachine-learningazure-machine-learningdeep-learning-libraryimaging
microsoft/CNTK
Oct 2016 - Nov 2016
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Role in this project:ML Engineer
ML EngineerContributions:15 commits, 3 PRs, 16 pushes in 27 days
Contributions summary:Anton contributed to the Microsoft Cognitive Toolkit (CNTK) by implementing and modifying the `EvaluateImage` and `EvaluateRgbImage` APIs. Their work included integrating bitmap data with the CNTK evaluation process, optimizing image processing loops, and cleaning up code. The user also made modifications to the C# example client and added error handling to the image APIs. These changes demonstrate a focus on improving the image evaluation capabilities and usability of the toolkit.
pytorchpythondeep-learningc-plus-plusmachine-learning
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.