Christian Bock
Senior Applied Scientist at Amazon Web Services (AWS)
Greater Seattle Area United States
Summary
👤
Senior🎓
Top SchoolChristian Bock is a Senior Applied Scientist with nine years of experience at the intersection of ML research and production, currently leading efforts at AWS to improve the trustworthiness of autonomous coding assistants and cross-language code issue localization. He holds a PhD from ETH Zurich where he developed deep learning and statistical methods for clinical EHR/ECG and graph-structured data, notably integrating topological data analysis into mainstream ML workflows. His background spans foundation model training optimizations (KV-caching, tensor parallelism), benchmark and metric design for code agents, and biomedical applications, reflecting a rare blend of systems engineering and domain-driven research. Based in the Greater Seattle Area, he builds next-generation developer experiences powered by LLMs while mentoring teams and streamlining experimental infrastructure. An understated through-line in his career is weaving healthcare-grade rigor into scalable ML systems, enabling practical impact from clinical data to developer tools.
9 years of coding experience
3 years of employment as a software developer
Master’s Degree, Medical Informatics, final Grade: 1.1, Master’s Degree, Medical Informatics, final Grade: 1.1 at Heidelberg UniversityDoctor of Sciences (ETH) - PhD, Machine Learning and Healthcare, Doctor of Sciences (ETH) - PhD, Machine Learning and Healthcare at ETH Zurich
English, German
Github Skills (91)
python10
topological-data-analysis10
deep-learning10
gpu10
ml10
neural-network10
classification10
tensorflow10
subsequence10
machine-learning10
multi-task-learning10
deep-neural-networks10
d3-force9
numpy9
audio9
Programming languages (8)
Github contributions (5)
chrisby/torchMTL
Oct 2020 - Feb 2021
A lightweight module for Multi-Task Learning in pytorch.
Contributions:1 release, 56 commits, 21 pushes in 3 months
multi-task-learningpytorchdeep-learningframeworkpython3
BorgwardtLab/WTK
Oct 2019 - Jun 2022
A Wasserstein Subsequence Kernel for Time Series.
Contributions:7 commits, 1 PR, 5 pushes in 2 years 8 months
kernelsubsequencetime-seriestime-series-classificationmachine-learning
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