I am a Machine Learning/Computer Vision Scientist at Genedata AG. Before, I was a Ph.D. student advised by Prof. Volker Roth and Prof. Thomas Vetter at the Department of Mathematics
and Computer Science at the University of Basel, Switzerland. Prior to that, I obtained my M.Sc. degree from Karlsruhe Institute of Technology (KIT) in Computer Science with a major in Software Engineering and Machine Learning.
My work is focused on developing robust and reliable machine learning systems that analyze high-content screening assays, primarily based on imaging data, to support world-leading biopharma companys in their early drug discovery process.
Recent News
Mar 2022: I will be a program committee member for the ML for Drug Discovery workshop at ICLR
Mar 2022: Our paper on self-supervised learning for HCS was accepted in MIDL
Feb 2022: Our poster on automated model selection of SPR production screens in collaboration with Amgen was presented at SLAS
Dec 2021: I co-organized the "ML Research to Clinical Practice" workshop at NeurIPS
Oct 2021: I co-organized and co-chaired a rountable with Roche and AstraZeneca on AI and automation of high-content screening analysis at SBI2
Aug 2021: Our paper on conditional invariance using cycle-consistency was accepted at GCPR
June 2021: Our poster on the robustness of Imagence was accepted at SLAS EU
Publications
Paper
Please have a look at my Google Scholar page for the complete list.
Self-Supervised Representation Learning for High-Content Screening
Daniel Siegismund*, Mario Wieser*, Stephan Heyse, Stephan Steigele
Medical Imaging with Deep Learning (MIDL), 2022
Learning Conditional Invariance through Cycle Consistency
Maxim Samarin*, Vitali Nesterov*, Mario Wieser, Aleksander Wieczorek, Sonali Parbhoo, Volker Roth
German Conference on Pattern Recognition (GCPR), 2021
Learning Extremal Representations with Deep Archetypal Analysis
Sebastian Keller, Maxim Samarin, Fabricio Arend Torres, Mario Wieser, Volker Roth
International Journal of Computer Vision (IJCV), 2021
Inverse Learning of Symmetries Mario Wieser, Sonali Parbhoo, Aleksander Wieczorek and Volker Roth
Neural Information Processing Systems (NeurIPS), 2020
Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment
Christian W. Thorball*, Alessandro Borghesi*, Nadine Bachmann, Chantal von Siebenthal, Valentina Vongrad, Teja Turk, Kathrin Neumann, Niko Beerenwinkel, Jasmina Bogojeska, Volker Roth, Yik Lim Kok, Sonali Parbhoo, Mario Wieser, Jürg Böni, Matthieu Perreau, Thomas Klimkait, Sabine Yerly, Manuel Battegay, Andri Rauch, Patrick Schmid, Enos Bernasconi, Matthias Cavassini, Roger D. Kouyos, Huldrych F. Günthard, Karin J. Metzner, Jacques Fellay and the Swiss HIV Cohort Study
Journal of Acquired Immune Deficiency Syndromes (JAIDS), 2020
Transfer Learning from Well-Curated to Less-Resourced Populations with HIV
Sonali Parbhoo, Mario Wieser, Volker Roth, Finale Doshi-Velez
Machine Learning for Healthcare (MLHC), 2020
Information Bottleneck For Estimating Treatment Effects With Systematically Missing Covariates
Sonali Parbhoo; Mario Wieser; Aleksander Wieczorek; Volker Roth
Entropy, 2020
Determinants of HIV-1 Reservoir Size and Long-Term Dynamics During Suppressive ART
SNadine Bachmann, Chantal von Siebenthal, Valentina Vongrad, Teja Turk, Kathrin Neumann, Niko Beerenwinkel, Jasmina Bogojeska, Jacques Fellay, Volker Roth, Yik Lim Kok, Christian Thorball, Alessandro Borghesi, Sonali Parbhoo, Mario Wieser, Jurg Böni, Matthieu Perreau, Thomas Klimkait, Sabine Yerly, Manuel Battegay, Andri Rauch, Matthias Hoffmann, Enos Bernasconi, Matthias Cavassini, Roger Kouyos, Huldrych Günthard, Karin Metzner, and Swiss HIV Cohort Study
Nature Communications, 2019
Deep Archetypal Analysis
Sebastian Keller, Maxim Samarin, Mario Wieser, Volker Roth
German Conference on Pattern Recognition (GCPR), 2019
Greedy Structure Learning of Hierarchical Compositional Models
Adam Kortylewski; Aleksander Wieczorek; Mario Wieser; Clemens Blumer; Sonali Parbhoo; Andreas Morel-Forster; Volker Roth and Thomas Vetter
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Learning Sparse Latent Representations with the Deep Copula Information Bottleneck
Aleksander Wieczorek*, Mario Wieser*, Damian Murezzan and Volker Roth
International Conference on Learning Representations (ICLR), 2018
A modular prototyping hard-and software platform for faster development of intelligent charging infrastructures of electric vehicles
Jan Clement, Mario Wieser, Pascal Benoit, Robert Kohrs and Christof Wittwer
IEEE Fourth International Conference on Power Engineering, Energy and Electrical Drives (POWERENG),2013