Oliver Wieder

After completing his Dipl.-Ing. degree with distinction in 2016, Oliver Wieder began his career as a software developer at Inte:Ligand GmbH (Vienna), where he worked until 2018. He then embarked on his Ph.D. program with the Cheminformatics Research Group at the Department of Pharmaceutical Chemistry, in collaboration with Laboratoires Servier (France) and Inte:Ligand GmbH. His primary research area focused on the development of AI-guided applications for early drug discovery, particularly graph-based deep learning methods for lead optimization.

In 2020, he began his work with Biolyz. By mid-2021, he co-founded Biolyz GmbH where he serves as the CTO and Head of AI&Data Science.

Oliver successfully completed his Ph.D. program with distinction in April 2022 and subsequently assumed the role of Senior Post-Doc at the Christian-Doppler Laboratory for Molecular Informatics in the Biosciences, collaborating with BASF SE and Boehringer Ingelheim RCV, starting in July 2022.

In addition to his research and entrepreneurial pursuits, Oliver actively contributes to the scientific community by serving as a reviewer for esteemed publications such as Natural Machine Intelligence (Nature), Journal of Cheminformatics, Journal of Chemical Information and Modeling, and Communications Chemistry. Furthermore, he is involved in teaching activities at the University of Vienna.

Room: 2E 357

Teaching: https://ufind.univie.ac.at/de/person.html?id=103635

AI Certification Course: https://www.postgraduatecenter.at/en/programs/communication-media/deep-learning-for-industrial-ai/

Google Scholar: https://scholar.google.com/citations?user=w5jecF8AAAAJ&hl=en

ORCID: orcid.org/0000-0003-4967-7613

LinkedIn: www.linkedin.com/in/oliver-wieder-67814154

Jacob RA , Wieder O , Chen Y, Mazzolari A, Bergner A, Schleifer KJ et al. Site-of-Metabolism Prediction with Aleatoric and Epistemic Uncertainty Quantification. Journal of Chemical Information and Modeling. 2025 Aug 25;65(16):8462-8474. doi: 10.1021/acs.jcim.5c00762

Rose D , Wieder O , Seidel T , Langer T. PharmacoMatch: Efficient 3D Pharmacophore Screening via Neural Subgraph Matching. In The Thirteenth International Conference on Learning Representations. 2025

Rose D , Wieder O , Seidel T , Langer T. PharmacoMatch: Efficient 3D Pharmacophore Screening through Neural Subgraph Matching. 2024 Sept 10.

Seidel T , Permann C , Wieder O, Kohlbacher SM, Langer T. High-Quality Conformer Generation with CONFORGE: Algorithm and Performance Assessment. Journal of Chemical Information and Modeling. 2023 Sept 11;63(17):5549-5570. doi: 10.1021/acs.jcim.3c00563

Seidel T , Permann C , Wieder O, Kohlbacher SM, Langer T. High-Quality Conformer Generation with CDPKit/CONFORT: Algorithm and Performance Assessment. 2022 May 13. doi: 10.21203/rs.3.rs-1597257/v1

Mayr F, Wieder M, Wieder O , Langer T. Improving Small Molecule pKa Prediction Using Transfer Learning With Graph Neural Networks. Frontiers in Chemistry. 2022 May 1;10:866585. doi: 10.1101/2022.01.20.476787, 10.3389/fchem.2022.866585, 10.3389/fchem.2022.866585

Wieder O, Kuenemann M, Wieder M, Seidel T, Meyer C, Bryant SD et al. Improved lipophilicity and aqueous solubility prediction with composite graph neural networks. Molecules. 2021 Oct 1;26(20):6185. doi: 10.3390/molecules26206185

Lubec J, Kalaba P, Hussein AM, Feyissa DD, Kotob MH, Mahmmoud RR et al. Reinstatement of synaptic plasticity in the aging brain through specific dopamine transporter inhibition. Molecular Psychiatry. 2021 Jul;26(12):7076-7090. doi: 10.1038/s41380-021-01214-x

Garon A, Wieder O, Bareis K, Seidel T, Ibis G, Bryant S et al. Hierarchical Graph Representation of Pharmacophore Models. Frontiers in Molecular Biosciences. 2020 Dec 14;7:599059. doi: 10.3389/fmolb.2020.599059, 10.3389/fmolb.2020.599059

Wieder O, Kohlbacher S, Kuenemann M, Garon A, Ducrot P, Seidel T et al. A compact review of molecular property prediction with graph neural networks. Drug Discovery Today: Technologies. 2020 Dec;37:1-12. doi: 10.1016/j.ddtec.2020.11.009

Seidel T , Wieder O, Garon A, Langer T. Applications of the Pharmacophore Concept in Natural Product inspired Drug Design. Molecular Informatics. 2020 Nov 1;39(11):2000059. doi: 10.1002/minf.202000059

Battisti V , Wieder O, Garon A, Seidel T , Urban E , Langer T. A Computational Approach to Identify Potential Novel Inhibitors against the Coronavirus SARS-CoV-2. Molecular Informatics. 2020 Oct;39(10):2000090. doi: 10.1002/minf.202000090

Dipl.-Ing. Dr. Oliver Wieder

Dipl.-Ing. Dr. Oliver Wieder