Leo Schwinn

Leo Schwinn, M. Sc.


Department Artificial Intelligence in Biomedical Engineering (AIBE)
Lehrstuhl für Maschinelles Lernen und Datenanalytik

Room: Room 01.016
Carl-Thiersch-Straße 2b
91052 Erlangen

Academic CV

02/2022 – 05/2022 Internship

Mila – Quebec AI Institute

Supervised by Doina Precup

 09/2019 – 11/2022 Researcher and PhD Candidate

Machine Learning and Data Analytics Lab,
Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

01/2019-03/2019 Scientific Assistant

IT Security Infrastructures Lab (CS1),
Department of Computer Science, Friedrich-Alexander-Universität (FAU)

10/2017-08/2019 M.Sc. in Medical Engineering, “Medical Image and Data Processing”

Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

Majors: Pattern Recognition, Machine Learning, Deep Learning
Master’s Thesis: “Learning Feature Extraction for End-to-End Speaker Recognition with Deep Neural Networks”

 10/2014-10/2017 B.Sc. in Medical Engineering, “Medical Imaging Systems”

Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

Majors: Pattern Recognition
Bachelor’s Thesis: “Unterscheidung von Sprachpathologien durch Sprechererkennungsverfahren”

Research Projects







Student Theses

Year Name Title
2022 Tim Löhr AI Trend Detection in Healthcare by applying Topic Clustering and Sentiment Analysis using Podcast Data
(Master’s Thesis, Co-Supervision)
2022 Andrey Kurzyukov Modeling Mixed-Type Time Series Data for Machinery Health Prognostics
(Master’s Thesis, Co-Supervision)
2021 Klaus Fischer Unsupervised Adversarial Representation Learning
(Master’s Project)
2021 Kenneth Mayer Improving Human Gait Analysis by Super-Resolution and Generative Adversarial Networks
(Master’s Project, Co-Supervision)
2021 Jonas Utz
Unsupervised Modeling of Visual Attention
(Master’s Project, Co-Supervision)
2021 Meike Biendl Exploring Connections between Visual Attention and Adversarial Robustness
(Master’s Thesis)
2021 Pavlo Beylin Simultaneous Classification and Identification of Adversarial Attacks Through Multi-Task Learning
(Master’s Thesis)
2021 Johannes Roider
Modeling Mixed-Type Time Series Data With Neural Networks for Predictive Maintenance
(Master’s Thesis, Co-Supervision)
2021 Tassilo Elsberger Analysis of Artificial Intelligence Trends in German Economics and Politics – A Data-Driven Approach
(Master’s Thesis, Co-Supervision)
2021 Miaomiao Li Adaptive Lipschitz Regularization of Neural Networks through Matrix Decomposition
(Master’s Thesis)
2021 Long Do Artificial Intelligence trend analysis using speech-to-text data from healthcare podcasts
(Master’s Thesis, Co-Supervision)
2020 Pavlo Beylin Development of a Modular Adversarial Attack Framework and Evaluation on the Sampled Nonlocal Gradient Descent Method
(Master’s Project)
2020 Osman Demir group:Anomaly Semantic Segmentation with Learnable Wavelet Filters
(Master’s Thesis)
2020 Darko Boshkovski group:Using speech recognition techniques for the application of online handwriting recognition
(Bachelor’s Thesis, Co-Supervision)