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.

The icons above 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

2021-04-06: Our work Stable Topological Signatures for Metric Trees through Graph Approximations was accepted for publication in Pattern Recognition Letters. A great Belgian–Swiss collaboration with Robin Vandaele, Yvan Saeys, and Tijl De Bie.
2021-04-04: Our work Exploring epithelial-cell calcium signaling with geometric and topological data analysis was accepted as a poster presentation at the Workshop on Geometrical and Topological Representation Learning at ICLR 2021.
2021-03-17: Honoured to serve as a technical programme committee member for the Topological Data Analysis and Its Application for Medical Data Workshop at MICCAI 2021.
2021-01-08: Our work Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis was accepted for publication in Applied Sciences. Congratulations and thanks to all collaborators on this very timely piece of work!
2021-01-03: Excited and honoured to co-organise a Workshop on Geometrical and Topological Representation Learning at ICLR 2021.
2020-12-07: Happy to talk about Recent Advances in Topology-Based Graph Classification in the Applied Mathematics Seminar of Yale University.
2020-11-20: Our work Topological Data Analysis of Copy Number Alterations in Cancer was accepted as an oral presentation at the LMRL Workshop at NeurIPS 2020! Joint work with Stefan Groha, Caroline Weis, and Alexander Gusev.
2020-11-12: Thrilled to talk about Machine learning for Personalised Medicine with Michael Moor at the Young Scientists Lunch Webinar Series, organised by the Swiss Society for Biomaterials and Regenerative Medicine.
2020-10-01: Super stoked to learn that our work Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence was accepted as a spotlight presentation at NeurIPS 2020!
2020-08-20: Excited and honoured to be organising a Workshop on Topological Data Analysis and Beyond at NeurIPS 2020!
2020-07-04: Our work Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis was accepted for publication in Travel Medicine and Infectious Disease. Thanks to all collaborators for this exciting project on a highly-relevant subject!
2020-07-03: Our work Enhancing statistical power in temporal biomarker discovery through representative shapelet mining was accepted for presentation at ECCB 2020.
2020-07-02: Happy to hear that our work Path Imputation Strategies for Signature Models was accepted for presentation at the Workshop on the Art of Learning with Missing Values (ARTEMISS) at ICML 2020.
2020-06-18: Our work Topological Methods for fMRI Data was accepted for presentation at the 2020 ICML Workshop on Computational Biology.
2020-06-11: Our workshop submission Kernel-based antimicrobial resistance prediction from MALDI-TOF mass spectra was accepted for a spotlight talk at the ML for Global Health Workshop at ICML 2020.
2020-06-01: Truly elated to see three papers accepted at ICML 2020: Graph Filtration Learning, Set Functions for Time Series, and Topological Autoencoders. A big thanks to all collaborators!
2020-04-14: Glad to see our work Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra accepted at ISMB 2020.
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!