University of Basel
Prof. Dr. Volker Roth
Department of Mathematics
and Computer Science
Room 06.003
Spiegelgasse 1
CH - 4051 Basel, Switzerland

Phone: + 41 61 207 0549
Fax: + 41 61 207 0559

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We work on machine learning and deep learning methods, with a focus on biomedical applications. Our activities include the development of statistical models for prediction, feature selection, clustering, network inference, but also image segmentation and causality mining. Currently we have research projects on identifying soil degradation in the Swiss Alps, modelling bird migration, and discovering novel molecules with desirable properties. In previous research projects we worked on EEG analysis in the context of Parkinson dementia, on DNA sequence analysis for HIV therapy optimization, on copula distributions and on causal models.


21. November 2022

We congratulate our group member Maxim Samarin for successfully defending his Ph.D. on "Machine Learning for Informed Representation Learning"!

21. July 2022

We congratulate our group member Daniel Hauke for successfully defending his Ph.D. on "Hierarchical Bayesian Inference in Psychosis"!

20. May 2022

Our paper on "Feature Learning and Random Features in Standard Finite-Width Convolutional Neural Networks: An Empirical Study" (paper, OpenReview) got accepted at the Conference on Uncertainty in Artificial Intelligence (UAI 2022), taking place in Eindhoven, 1st to 5th August 2022.

3. March 2022

The Swiss National Science Foundation (SNSF) produced a video on "Tracking soil erosion with Big Data" (in German; or with subtitles in English or French) for our weObserve project.

1. March 2022

We congratulate our former group member Sonali Parbhoo on starting her position as an Assistant Professor at Imperial College London.

6. February 2022

Volker Roth gives an invited talk in the AAAI-22 Workshop on Information-Theoretic Methods for Causal Inference and Discovery (1st of March).

1. February 2022

Marcello Negri joined our group as a new PhD student.

1. October 2021

Maxim Samarin presented our paper on "Learning Conditional Invariance Through Cycle Consistency" (paper, arXiv) at GCPR 2021. You can watch the talk here.

Who we are