I am a PhD candidate at the Institute of Medical Informatics at RWTH Aachen University. Previously, I carried out research at Research Center Jülich and at the Charité in Berlin. I received my MSc (2022) and BSc (2019) in Biological Information Processing from RWTH Aachen.
My work focuses on machine learning for medicine, including multimodal clinical systems, trustworthy methods, and reliable evaluation for clinical deployment. My work spans medical imaging, text, and biosignals such as ECG, with an emphasis on robustness and real-world reliability.
Away from the screen, I finished a marathon in 4:56:40, a slow convergence, but it converged.
Institute of Medical Informatics, RWTH Aachen University · Aachen, Germany
Research Center Jülich (IBI-3) · Jülich, Germany
Charité Berlin — AG Klinische Neurotechnologie · Berlin, Germany
Molecular & Systemic Neurophysiology, RWTH Aachen · Aachen, Germany
RWTH Aachen University · Institute of Medical Informatics
RWTH Aachen University · Major: Computational Neuroscience
RWTH Aachen University · Aachen, Germany
LLM-integrated systems · Multimodal learning · LLM-based evaluation & scoring · Speech recognition · Speaker diarization · Behavioral and biosignal fusion · Retrieval-augmented generation
PyTorch · scikit-learn · Deep learning · Representation learning · Time-series modeling · Self-supervised learning · Algorithm design
Robustness · Reproducibility · Auditability · Differential privacy · Evaluation in high-stakes clinical settings · Model monitoring
Multicenter clinical evaluation · IRB-compliant workflows · Biosignal processing (ECG, EEG, accelerometry) · Dataset curation · Benchmarking
Python · MATLAB · Git · CUDA · HPC cluster environments · Docker · Weights & Biases · MLflow · Open-source research code
Production ML pipelines · Monitoring infrastructure · Reproducible workflows · Model lifecycle management
Reliable Detection of Focal Onset Impaired Awareness Seizures Using Wearable ECG
ECG Matching: Synchronizing ECG Datasets for Data Quality Comparisons
The Role of Self-Supervised Pretraining in Differentially Private Medical Image Analysis
Aachen, Germany
Open to collaborations on trustworthy medical-AI research, open-source ML tooling, and dependable deployment.