Hi, my name is
I'm currently pursuing a Master's degree in Artificial Intelligence and Intelligent Systems at the University of Bremen. My research specializes in Biosignal Processing, where I apply Machine Learning and Deep Learning to analyze complex physiological data and build intelligent architectures.
Developing predictive models and deep learning architectures for complex datasets, with a focus on biosignal processing (EEG, ECG, EDA).
Investigating security vulnerabilities and applying machine learning techniques to detect and mitigate emerging cyber threats.
Building scalable web platforms, experimental research frameworks, and multi-agent AI governance systems.
Machine Learning Pipeline
Actively involved in physiological data collection during VR trials and conducted deep experimental analysis of the data. Engineered a comprehensive preprocessing and ML pipeline for EEG, ECG, and EDA signals, employing Multinomial Logistic Regression and LASSO to classify neurological impairments.
AI Governance Framework
A centralized control plane for multi-agent quantitative research. Prevents AI confirmation bias by splitting responsibilities across architect, executor, and red-team critic agents, ensuring rigorous empirical validation.
Minds, Media, Machines (MMM)
Solely designed and orchestrated the complete experimental framework to analyze developers' cognitive activity using high-density EEG (256-channel) during program comprehension tasks. Employed Machine Learning models (Random Forests, Deep Learning) to classify cognitive states such as attention and mental workload in a software visualization environment.
Medical Imaging AI
A calibration-aware, recall-oriented evaluation of deep architectures (ConvNeXt, Swin Transformer, ViT, ResNet) for MRI classification. Implemented perceptual-hash pseudo-patient grouping to prevent data leakage and optimized decision thresholds for critical glioma recall.