معرفی
Dr. Alexander Schulz is a Researcher at the University of Bielefeld within the Faculty of Engineering and its Machine Learning Group. He focuses on machine learning applications across diverse domains including biomedical engineering, fairness evaluation, and data visualization.
- Research Interests
- Transfer learning for medical applications
- Dimensionality reduction techniques
- Bias detection in language models
- Classifier visualization tools
- Collaborations
- Center for Cognitive Interaction Technology (CITEC)
- Machine Learning Reports publications
His recent publications highlight trends in dynamic graph analysis, semantic bias measurement, and physiological data generation. He has contributed to tools like the Box and Beans test for prosthetics evaluation and DeepView for classifier boundary visualization. Collaborative projects include cardiovascular data synthesis for implantable devices and fairness-aware AI frameworks.
Dr. Schulz works at CITEC 2-228 and is reachable at aschulz@techfak.uni-bielefeld.de. His work integrates theoretical machine learning with practical implementations in healthcare and industrial systems.