Hello visitor! I am Mo, a researcher building LLM-powered AI for medicine, from model development and careful evaluation to deployment in real clinical settings.
I'm particularly interested in multimodal LLMs for clinical use, trustworthy AI in healthcare, and privacy-preserving ML for sensitive medical data. I'm currently pursuing a PhD at the Institute of Medical Informatics at RWTH Aachen University.
Away from the screen, I once finished a marathon in 4:56:40 — slow convergence, but it converged.
Institute of Medical Informatics, RWTH Aachen University · Aachen, Germany
Forschungszentrum 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.