Christian Bock
Senior Applied Scientist @ AWS
Coding Agents at AWS. Ph.D. in Machine Learning from ETH Zurich.
changelog
2026/02/05
New preprint: "SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization"
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2025/12/15
New preprint: "Textual Gradients are a Flawed Metaphor for Automatic Prompt Optimization"
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2025/04/23
New preprint: "SWE-PolyBench: A multi-language benchmark for repository level evaluation of coding agents"
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2024/06/12
Our work on diagnosing coronary artery disease with ML was published in Nature Communications.
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2022/11/01
I joined Amazon Web Services as an Applied Scientist.
2021/12/01
I started a new position as Solution Architect at Machine Learning Architects Basel.
2021/10/18
I successfully defended my PhD!
2021/03/02
I am a student organizer of the ICLR workshop on Geometrical and Topological Representation Learning
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2021/03/01
Successfully finished my AWS internship with a manuscript on time series anomaly detection using state space Gaussian processes. arXiv link to follow.
2021/03/01
I co-organize the Clinical Machine Learning Track of the EPFL Applied Machine Learning Days Series
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2020/11/02
Excited to continue my research on time series at Amazon as an Applied Scientist Intern.
2020/10/01
I started the fourth year of my PhD!
2020/09/26
Our NeurIPS submission on "Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence" was accepted as a spotlight.
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2020/09/02
I am happy to be part of the program committee of the "Topological Data Analysis and Beyond" workshop at NeurIPS 2020.
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2020/07/22
I started blogging my summaries of the MLSS lectures. The first one is about causality.
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2020/05/27
New preprint on time series imputation strategies.
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2020/04/29
I was lucky enough to got selected for participation at the Machine Learning Summer School 2020!
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2020/03/09
Our work on circulatory failure prediction in the ICU was published in Nature Medicine.
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2019/11/16
Published a new blog post about our Wasserstein Kernel for Time Series.
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2019/10/01
Our Wasserstein-based subsequence kernel for time series has been accepted at the Optimal Transport in Machine Learning (OTML) Workhop at NeurIPS.
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2019/10/01
I started the third year of my PhD!
2019/08/09
Our Wasserstein-based subsequence kernel for time series has been accepted at ICDM.
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2019/06/09
I published a blog article on persistent homology.
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2019/04/21
Our topological extension of the Weisfeiler-Lehman algorithm for graph classification has been accepted for poster presentation and a short talk at ICML.
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2019/03/17
I published my first blog article on S3M.
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2018/12/18
Our work on Neural Persistence has been accepted for poster presentation at ICLR.
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2018/10/01
I started the second year of my PhD!
2018/06/19
I presented our work on S3M at the Personalized Health Technologies Research Conference in Zurich.
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2018/03/01
Our work on association mapping in biomedical time series (S3M) was accepted at ISMB and published in Bioinformatics.
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2017/10/01
I started my PhD at ETH Zurich in Karsten Borgwardt's Group of Machine Learning and Computational Biology
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