Projects that we offer for master and bachelor students

If you are interested in working with us, send us email including information about relevant courses and projects that you have conducted, and your interests. 

External ressources
- Course on scientific writing
Thesis template, courtesy of Prof. Holger Dell 
Guidelines for bachelor thesis (B.S. bioinformatics)
Guidelines for master thesis (M.S. bioinformatics)

Completed Master Theses

- Hoang Tu Ngo (2020), Understanding human visual perception by finding similarities between fMRI brain data and deep neural networks.

- Elias Poensgen (2021), Cross-Modal Learning and Generation using Generative Adversarial Nets.

- Lukas Licitar (2021), How does a new automated AI-technology change the role in client engagement, by SAP Concur and is it possible to derive a direct increase in revenue? Possible conclusion from KPIs and analysis. (At SAP Concur)

- Teresa Werthmann (2021), Ethical assessment of AI systems in healthcare: A use case.

- Frederike Laufenberg (2021), Ethical assessment of AI systems in healthcare: A use case.

- Daniel Pietschmann (2021), Single-task and multi-task transfer learning in a multi-source context.

- Yannic Vorpahl (2021), Single-task and multi-task transfer learning in a multi-source context.

- David Lüdke (2022). Neural Flow-based Deformations for Statistical Shape Modelling. (At Zuse Institute Berlin)

Completed Bachelor Theses

- Felix Nonnengießer (2020), Glancing at Images: Foveated Neural NetworksWith Recurrent Visual Attention for Image Recognition.

- Marius Bange (2020), Vimotion - A Webapp for emotion based matching of audio and video.

- Quang Anh Hong (2021), Influence of Training Dataset Resemblance to Stimulus Set on Prediction Accuracy of Brain Activity.

- Nizar Bikti (2021), Visual Features: Their Extraction and Linear Correlation to Emotional Dimensions.

- Carla Frenzel (2021), Predicting Human Brain Activity During Language Processing with the Help of Computational Language Processing Models.

- Sandesh Baral (2021), Keypoints regression of dance poses with Openpose and Neural networks based dance classification methods.

- Shivan Oskan (2021), A Web App to Analyse the Impact of Dance Videos on Emotion Perception by Viewing and Mood Regulation by Imitation.

- Yusuf Baran (2021), Which characteristics of a dance are responsible for the emotion the spectator feels?

- Domenic Bersch (2021), Towards a general library for deep learning models to understand the architecture of the visual cortex.

- Bipul Mani Pokhrel (2021), Feature Comparison of BERT Transfer Learning with autoencoder language models.

- Tomislav Vrdoljak (2021), A Machine Learning Approach Using Deep Learning to Evaluate Epileptic Treatment Based on EEG Data. (With Prof. Jochen Triesch)

- Max Krawietz (2021), Do Machine Learning classifiers have an innate fairness?

- Dirk Neuhäuser (2021), Contrastive Learning of Object Representations.

- Ali Poursotoudeh Tehrani (2021), Do Convolutional Neural Networks Encode Numerosity Information?

- Jonas Roemer (2022), Application of Genetic Algorithms to Generative Adversarial Networks.

Snizhana Fedchenko (2022). Management of Machine Learning Models for Estimation of Flight Risk of Employees. (At Merk KGaA)

- Tra Mi Thi Tran (2022), The influence of dataset biases on classification fairness.

- Matthias Fulde (2022). Predicting Neural Responses to Naturalistic Videos using Multimodal deep neural networks.

Johannes Bastian (2023). Development of Number Sense in Neural Networks in a Real World Environment.

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