Teaching

Lectures and Tutorials

University of Bremen

• SS 2023-2025: Lecture: Fundamentals of Machine Learning (Bachelor)

Leibniz University Hannover

• SS 2022: Lecture: Artificial Intelligence for Healthcare (Master)

University of Augsburg

WS 2020/21:

• Practicum Speech Pathology (Master)
• Tutorial of Speech Pathology (Master)

SS 2020:

• Seminar Computational Intelligence (Bachelor & Master)

WS 2019/20:

• Practicum Speech Pathology (Master) (Intensive one-week course)

SS 2019:

• Practicum Deep Learning (Master) (Intensive one-week course)

WS 2018/19:

• Practicum Mobile Sensing for Fitness and Wellbeing (Master) (Intensive one-week course)
• Tutorial of Speech Pathology (Master)

SS 2018:

• Practicum Mobile Application Development (Master)

WS 2017/18:

• Practicum Mobile Sensing for Fitness and Wellbeing (Master) (Intensive one-week course)

Supervision

PhD mentoring

• Mira Richts, “Delirium detection from speech”, University of Bremen, Co-supervision with Prof. Tanja Schultz, since 2025
• Rathi Adarshi Rammohan, “Hate speech detection”, University of Bremen, Co-supervision with Prof. Tanja Schultz, 2023-2027
• Kevin Scheck, “Electromyography to speech conversion”, University of Bremen, Co-supervision with Prof. Tanja Schultz, 2023-2026
• Peter , “Industrial sound analysis”, Leibniz University Hannover, Co-supervision with Prof. Wolfgang Nejdl, 2022-2026
• Yi Chang, “Computer audition for respiratory and mental health”, Imperial College London, Co-supervision with Prof. Björn Schuller, 2020-2025

Bachelor / Master supervision

• Jonas Geschonke, “Silent speech interfaces”, Master thesis, University of Bremen, 2026.
• Paul Bernhard, “Hate speech detection”, Master thesis, University of Bremen, 2026.
• Sarai Lopez Quezada, “Analysis of Individual Speaker Features on Group-level Emotion Recognition from Speech”, Master thesis, co-supervise, 2025
• Wei Wang, “Towards Automatic Heart Sound Segmentation”, Master thesis, Leibniz University Hannover, 2022.
• Hao Yu, “Automated Audio Captioning with Transformer”, Master thesis, Leibniz University Hannover, 07/2022-12/2022.
• Tianyi Zhou, “Multi-task Learning with Attention-based Task Relationship Modeling for COVID-19 Cough Sound Analysis”, Master thesis, Leibniz University Hannover, 2022.
• Guanqiao Sui, “Skeptical Learning for Sound Classification”, Master thesis, Leibniz University Hannover, 2022
• Mohammad Mehdi Zahed, “Interpretable machine learning for sound classification”, Master thesis, Leibniz University Hannover, 2022

This work was published in IJCNN: Z. Ren, T. T. N. Nguyen, M. M. Zahed, and W. Nejdl, “Selfexplaining neural networks for respiratory sound classification with scale-free interpretability,” in Proc. IJCNN, (Gold Coast, Australia), 2023.

• Quang Phu Quang, “Multitask learning with attention-based task relationship modelling for COVID-19 cough sound analysis”, Master thesis, Leibniz University Hannover, 2022
• Fabio Hellmann, “Deformable faster-RCNN for lesion detection in CT images”, Master thesis, University of Augsburg, 07/2020-11/2020.

This work was published in EMBC: F. Hellmann, Z. Ren, E. Andre, and B. Schuller, “Deformable dilated faster R-CNN for universal lesion detection in CT images,” in Proc. EMBC, (Virtual), pp. 2896–2902, 2021.

• Dennis Zürn, “Investigation of explainable AI techniques for computational paralinguistics”, Master thesis, University of Augsburg, 08/2020-07/2021.
• Yang Tian, “Adversarial attacks: A threat to deep speech-based end-to-end models for healthcare”, Master thesis, University of Augsburg, 10/2020-07/2021.