Bastian Rieck

Welcome to my personal and academic space! I am a senior assistant in the Machine Learning & Computational Biology Lab of Prof. Dr. Karsten Borgwardt at ETH Zürich.

Previously, I obtained my Ph.D. in computer science from Heidelberg University, which is where I also got my diploma in mathematics. This site contains some things I care about.

I can be reached at:

Building BSB, room 2/001
Mattenstrasse 26
4058 Basel
Switzerland

The icons below should cover everything, but in case you prefer text: a current academic curriculum vitæ is available. My ORCID is 0000-0003-4335-0302. I also have a Google Scholar profile, a ResearchGate profile, a publons profile, and a GitHub account. Sometimes, I tweet things.

News

2020-03-09: Happy to see that our paper Early prediction of circulatory failure in the intensive care unit using machine learning was published in Nature Medicine!
2019-12-20: I am honoured to have been invited to give a talk on topology-based graph classification at the AI & Topology track of the Applied Machine Learning Days at EPFL.
2019-12-10: I created a Slack community for discussing topological machine learning. Please join TDA in ML if you are interested!
2019-11-18: I am honoured to receive a Spark grant from the Swiss National Science Foundation to fund my proposal TOPAZ: Topology of Alzheimer’s.
2019-11-07: Our work Sparse representations for MALDI-TOF based microbial classification was accepted as a poster presentation at the Machine Learning and Computational Biology Meeting (MLCB).
2019-11-01: Our work Topological Autoencoders has been accepted for an oral presentation at the Swiss Machine Learning Day 2019 (SMLD).
2019-09-27: I am truly honoured to serve as a mentor for the New in ML 2019 Workshop among so many of my role models.
2019-09-16: The slides for my keynote talk at the Applications of Topological Data Analysis Workshop are now available.
2019-09-04: I am delighted to receive an outstanding reviewer award for the ECMLPKDD 2019 Journal Track.
2019-09-03: Our work Wasserstein Weisfeiler–Lehman Graph Kernels has been accepted at NeurIPS 2019 with a spotlight presentation.
2019-09-03: I am honoured to receive a free NeurIPS 2019 registration for being an outstanding reviewer.
2019-08-09: Our work A Wasserstein Subsequence Kernel for Time Series has been accepted at the IEEE International Conference on Data Mining (ICDM).
2019-08-01: Four new preprints have been added. They will become chapters of the upcoming book Topological Methods in Data Analysis and Visualization V.
2019-07-06: Our work Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping has been accepted for a poster presentation and a spotlight talk at the Machine Learning for Healthcare conference (MLHC).
2019-05-20: I am honoured to have been invited to give a keynote talk at the Applications of Topological Data Analysis Workshop, co-located with ECMLPKDD 2019.
2019-04-21: Our work A Persistent Weisfeiler–Lehman Procedure for Graph Classification has been accepted for a poster presentation and a short talk at the International Conference for Machine Learning (ICML).
2018-12-18: Our work Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology has been accepted for a poster presentation at the International Conference for Learning Representations (ICLR).