Dr. Sören Wacker

Delft Technical University, The Netherlands

Leading computational infrastructure and data science initiatives across multiple research domains. CropXR Research Engineer and Technical Consultant for large-scale agriculture project. Developing deep learning POC for cell detection and classification (SCENNIA). HPC cluster support including deployment of Open OnDemand applications & SLURM usage dashboards. Developing and delivering workshops on best practices for HPC systems.

University of Calgary, Canada

Led data science team for world's largest multi-omics project managing 35,000 samples across genomics, proteomics, and metabolomics (100TB+ data). Built automated proteomics data pipeline reducing scientist QC time by 98%. Developed web GUI for large-scale metabolomics processing (ms-mint-app). Supervised and trained PhD students while serving as technical advisor for start-up Fluidome.

University of Calgary, Canada

Implemented Python library for scalable metabolomics (ms-mint). Mentored PhD students through code reviews and in-person support. Applied deep learning methods to diverse datasets for scientific discovery. Maintained GitHub repositories for research groups.

Georg-August University & Max Planck Institute for Biophysical Chemistry

Conducted Molecular Dynamics Simulations for Computer-Aided Drug Design. Performed molecular docking studies. Developed MySQL database schema for storage of large-scale molecular docking results.

Specialized in ion-channel research and drug discovery through computational modeling

Georg-August University

Specialization in computational physics with focus on molecular simulations

Foundation in theoretical and computational physics

Leibniz University Hannover

Undergraduate foundation in physics and mathematics

Core physics and mathematical principles

Achlys-Inc

Co-founded startup with Li Ka Shing Institute focusing on machine learning for drug discovery. Created ML model for prediction of cardiac toxicity of novel drug candidates with patent application. Achieved top 10% in Kaggle 'Rossmann Store Sales' competition using XGBoost.

€6,000 in compute resources for climate-adaptive agriculture research platform

~$120,000 in compute resources for multi-omics data processing

~$300,000 in compute resources for large-scale genomics and metabolomics analysis

Through a solid foundation of Dutch plant biology, agricultural sciences, and plant breeding, the institute adds an integrated layer of experimental research, artificial intelligence and computational modelling to develop technology and methods for new crop varieties better adjusted to climate change.

Developed browser-based proof-of-concept for microbial image processing featuring single-cell segmentation and classification. This demo application showcases advanced computer vision techniques for automated analysis of microbial cells.

This comprehensive dataset links genomics, proteomics, and metabolomics data with detailed patient records, creating unprecedented research opportunities in antimicrobial resistance and personalized medicine.

Developed and implemented Python library for scalable metabolomics data processing. The platform includes both command-line tools and web GUI (ms-mint-app) for comprehensive metabolomics workflows.

Web application for automating absolute quantification of mass spectrometry-based metabolomics data. Published in Analytical Chemistry, this platform provides researchers with robust, automated tools for metabolomics quantification.

Co-founded startup with Li Ka Shing Institute focusing on machine learning applications for drug discovery. Developed machine learning models for prediction of cardiac toxicity of novel drug candidates, resulting in patent application.

Ponce LF, Bishop SL, Wacker S, Groves RA, Lewis IA

Analytical Chemistry

Web application for automated quantification workflows in metabolomics research

Brown K, Thomson CA, Wacker S, Groves R, Fan V, Lewis IA, McCoy KD

Nature Communications

Large-scale metabolomics study demonstrating microbiome impact on host metabolism

Bishop SL, Drikic M, Wacker S, Chen Y, Kozyrskyj A, Lewis IA

Mucosal Immunology

Review paper on metabolomics applications in microbiome research

Lee K, Fant AD, Guo J, et al., Wacker S, et al.

Journal of Chemical Information and Modeling

ML-guided drug design for reduced cardiac toxicity

Wacker S, Noskov SY

Computational Toxicology

Comprehensive evaluation of ML approaches for cardiac safety prediction

Delft University of Technology

Developed and delivered workshops including: Scalable Machine Learning on DelftBlue and DAIC, Introduction to Apptainer, Python Projects: Reproducibility & Automation

University of Calgary

8-week university course with practical hands-on lessons in Python coding for Data Science and Machine Learning applications in biology

Niagara, Canada

Presented research on automated metabolomics workflows

Calgary, Canada

Sergei Noskov Memorial Symposium keynote presentation

San Francisco, USA

Data science and machine learning applications

Briefings in Bioinformatics

Scientific manuscript review and evaluation

Journal of Chemical Information and Modeling

Scientific manuscript review in computational chemistry and drug discovery

Multiple Institutions

Supervised and mentored PhD students in computational biology and data science

Wacker S, Lewis IA

Comprehensive software package for scalable metabolomics data processing