Kyriakos Soulios
PhD Candidate - Data Scientist
Helmholtz Centre for Environmental Research - UFZ
Department Computational Biology
Permoserstr. 15, 04318 Leipzig, Germany
Building: Building 4.1
Room: Room 237
Email: kyriakos.soulios@ufz.de
Research interests
- Computational toxicology
- Graph Neural networks
- Unsupervised / Semi-Supervised learning
- Contrastive learning
- Molecular Representations
- Uncertainty Quantification
- Conformal Prediction
Scientific Network
Current Projects
Toxicity prediction mining the chemical universe.
The goal of the project is to provide accurate and trustworthy ML models which can predict the toxicity of chemical found in the environment. The larger scope of the project consists of:
- Prioritize the toxicity assessment of chemicals in the environment
- Monitor/Regulate the suspected substances
- Design "green" chemicals
The second leg of the project focuses more in the trustworthiness of the developed ML models by integrating Uncertainty Quantification methods and exAI techniques and analysing into the actual predictions and explanations.
Keywords: Computational toxicology, Graph Neural Networks, Molecular Property prediction, Uncertainty Quantification
Academic Career
09/2021 - Current: Doctoral Researcher in Bioinformatics,
Department of Computational Biology, Helmholtz Centre of Environmental Research
09/2021 - Current: PhD Candidate in Bioinformatics, Faculty of Mathematics and Computer Science, University of Leipzig, Germany
10/2015 - 02/2021: Integrated Master's in Cheminformatics, Faculty of Pharmacy, National and Kapodistrian University of Athens, Greece
Publications
Grants & Awards
- Helmholtz Institute for Data Science Trainee Network Grant: 6000€ for a 3-month research stay working on Topology-guided GNNs for toxicity prediction