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Current Theses for all TIK GroupsB = Bachelor, G = Group, M = Master, S = Semester |
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| title | category | type | contact/supervisor | assigned | student(s) | thesis number | edit | |
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Eigenvector-Masked Autoencoders | B | Till Aczel, Andreas Plesner |
FS 25 | BA-2025-15 |   |
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Aggregation in Team Games | M | Andrei Constantinescu, Borna Simic |
FS 25 | MA-2025-06 | |
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| AlphaZero Meets ARC | M | Andreas Plesner, Benjamin Estermann |
FS 25 | MA-2025-07 | |
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ARC Literature Review | S | Andreas Plesner | FS 25 | SA-2025-08 | |
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Asynchronous Graph Neural Network Models | B | Florian Grötschla | FS 25 | BA-2025-09 | |
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Audio Upmixing | M | Luca Lanzendörfer, Florian Grötschla |
FS 25 | MA-2025-08 | |
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Beatmaker | S | Luca Lanzendörfer, Florian Grötschla |
FS 25 | SA-2025-12 | |
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Context-Aware In- Car Recommender System: Predicting UI Interactions (User Needs) with Driving Context | M | Andreas Plesner | FS 25 | MA-2025-16 | |
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Contrastive Decoding | M | Luca Lanzendörfer, Frédéric Berdoz |
FS 25 | MA-2025-15 | |
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Creating the Next Decentralized Computer | B | Anton Paramonov, Yann Vonlanthen |
FS 25 | BA-2025-05 | |
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Data Attribution | B | Luca Lanzendörfer, Frédéric Berdoz |
FS 25 | BA-2025-04 | |
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Deep Differentiable Logic Gate Networks: Neuron Collapse Through a Neural Architecture Search Perspective | S | Andreas Plesner, Till Aczel |
FS 25 | SA-2025-11 | |
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Designing the Next ARC Challenge | M | Saku Peltonen, Andreas Plesner |
FS 25 | MA-2025-01 | |
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DiffLogic - Recurrent Networks | S | Till Aczel, Andreas Plesner |
FS 25 | SA-2025-15 | |
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Effectiveness of Multi-Scale Aggregation for Adversarial Robustness | B | Andreas Plesner, Till Aczel |
FS 25 | BA-2025-16 | |
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Empirical Analysis of Blockchain Payment Systems | B | Saku Peltonen, Lioba Heimbach |
FS 25 | BA-2025-02 | |
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Enhancing AlphaZero with Neural Message Passing | S | Samuel Dauncey, Saku Peltonen |
FS 25 | SA-2025-07 | |
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Evaluating AI-Generated Image Detection Across Resolution and Complexity | B | Till Aczel, Andreas Plesner |
FS 25 | BA-2025-12 | |
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Evaluating and Controlling the Political Bias of LLMs | M | Frédéric Berdoz | FS 25 | MA-2025-04 | |
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Exploring adversarial concepts | S | Andreas Plesner | FS 25 | SA-2025-03 | |
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Fake Singing Voice Detection | M | Luca Lanzendörfer, Florian Grötschla |
FS 25 | MA-2025-05 | |
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Faster DiffLogic | S | Andreas Plesner, Till Aczel |
FS 25 | SA-2025-10 | |
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Graph Autoencoder | M | Florian Grötschla, Saku Peltonen |
FS 25 | MA-2025-09 | |
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Image-to-Prompt | B | Frédéric Berdoz, Luca Lanzendörfer |
FS 25 | BA-2025-14 | |
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Impact of Training Data on Adversarial Examples | B | Andreas Plesner, Till Aczel |
FS 25 | BA-2025-13 | |
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Increasing Expressiveness of DiffLogic | S | Andreas Plesner, Till Aczel |
FS 25 | SA-2025-14 | |
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Interpreting the Reversal Curse of LLMs | M | Samuel Dauncey | FS 25 | MA-2025-12 | |
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IQ of VLMs – can they really reason? | B | Andreas Plesner, Frédéric Berdoz |
FS 25 | BA-2025-11 | |
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LLM Sampling Methods | B | Frédéric Berdoz, Andreas Plesner |
FS 25 | BA-2025-10 | |
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Mesh Optimization and Neural Closure Modeling Using Graph Neural Networks | M | Florian Grötschla, Joël Mathys |
FS 25 | MA-2025-10 | |
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MEV on Solana | M | Lioba Heimbach | FS 25 | MA-2025-11 | |
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ML for Fashion | M | Luca Lanzendörfer, Till Aczel |
FS 25 | MA-2025-03 | |
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More Efficient Transformers with high-level multi-token prediction | B | Frédéric Berdoz, Benjamin Estermann |
FS 25 | BA-2025-06 | |
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Multi-Lingual Text-to-Speech Dataset | B | Luca Lanzendörfer, Florian Grötschla |
FS 25 | BA-2025-08 | |
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Multimodal Graph-Language Models | S | Florian Grötschla, Saku Peltonen |
FS 25 | SA-2025-04 | |
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NeRF to evaluate Robustness | M | Andreas Plesner, Till Aczel |
FS 25 | MA-2025-14 | |
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Neural Amp modelling | S | Florian Grötschla, Luca Lanzendörfer |
FS 25 | SA-2025-13 | |
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Ranking Movies with LLMs | B | Luca Lanzendörfer, Frédéric Berdoz |
FS 25 | BA-2025-07 | |
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Reasoning Benchmark for LLMs | B | Benjamin Estermann, Luca Lanzendörfer |
FS 25 | BA-2025-03 | |
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Recopmression | B | Till Aczel | FS 25 | BA-2025-01 | |
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Robust Multi-lingual Speaker Diarization | S | Luca Lanzendörfer, Florian Grötschla |
FS 25 | SA-2025-05 | |
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RSTAR Meets ARC | B | Andreas Plesner, Benjamin Estermann |
FS 25 | BA-2025-17 | |
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Sample Efficiency in Text Diffusion Pretraining | S | Samuel Dauncey | FS 25 | SA-2025-09 | |
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Scalable Proof-of-Personhood | B | Yann Vonlanthen | FS 25 | BA-2025-19 | |
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Scalar Quantization for Audio Compression | S | Till Aczel, Luca Lanzendörfer |
FS 25 | SA-2025-01 | |
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Scaling laws for test-time compute with SID.ai | M | Samuel Dauncey | FS 25 | MA-2025-17 | |
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Simulating Democracy through LLM Agents | M | Frédéric Berdoz, Yann Vonlanthen |
FS 25 | MA-2025-13 | |
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Speech Dataset Pipeline | B | Luca Lanzendörfer, Florian Grötschla |
FS 25 | BA-2025-20 | |
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Synthetic Data as a Data Augmentation | B | Andreas Plesner, Till Aczel |
FS 25 | BA-2025-18 | |
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Text-to-Scene | S | Luca Lanzendörfer, Frédéric Berdoz |
FS 25 | SA-2025-06 | |
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Video-to-Audio Generation | M | Luca Lanzendörfer, Florian Grötschla |
FS 25 | MA-2025-02 | |
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Audio Editing | M | Luca Lanzendörfer, Florian Grötschla |
HS 24 | MA-2024-35 | |
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Audio Watermarking | M | Luca Lanzendörfer, Florian Grötschla |
HS 24 | MA-2024-37 | |
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Chaos Testing Blockchain Networks: Simulating Real-World Failures | M | Yann Vonlanthen | HS 24 | MA-2024-32 | |
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DAO Governance Aggregation | B | Arthur Gervais | HS 24 | BA-2024-11 | |
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DeepEye: Benchmarking & Generalization | B | Ard Kastrati | HS 24 | BA-2024-20 | |
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DeepEye: Benchmarking Platform | B | Ard Kastrati | HS 24 | BA-2024-19 | |
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Egocentric Action Recognition | M | Ard Kastrati | HS 24 | MA-2024-21 | |
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Foundation Models for Decoding Brain Activity - Benchmarking | B | Ard Kastrati | HS 24 | BA-2024-24 | |
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Foundation Models for Decoding Brain Activity - Models | M | Ard Kastrati | HS 24 | MA-2024-33 | |
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Giving ChatGPT a Virtual Body | S | Ard Kastrati | HS 24 | SA-2024-26 | |
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Layer-2s and MEV | B | Lioba Heimbach, Yann Vonlanthen |
HS 24 | BA-2024-29 | |
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Multi-modal Contrastive Learning for Emotion Recognition | M | Ard Kastrati | HS 24 | MA-2024-31 | |
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Neural Fluid Simulation with GNNs | S | Joël Mathys, Florian Grötschla |
HS 24 | SA-2024-23 | |
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Optimizing Encoding Speed for Image Compression | M | Till Aczel | HS 24 | MA-2024-36 | |
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Optimizing Inventory Management | M | Andreas Plesner, Benjamin Estermann |
HS 24 | MA-2024-38 | |
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SAT Solving with Graph Neural Networks | S | Saku Peltonen, Joël Mathys |
HS 24 | SA-2024-30 | |
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Stability of Adversarial Examples | B | Andreas Plesner | HS 24 | BA-2024-27 | |
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Stock Market Prediction | M | Joël Mathys, Ruedi Delacour |
HS 24 | MA-2024-34 | |
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View-Specific Video Compression | B | Till Aczel | HS 24 | BA-2024-25 | |
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Volatility Forecasting and Regime Detection for Options Trading | M | Frédéric Berdoz, Ruedi Delacour |
HS 24 | MA-2024-29 | |
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Game Theory for Games: Algorithms and Axioms | G | Andrei Constantinescu | FS 24 | GA-2024-03 | |
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Karma Economics | S | Damien Berriaud | FS 24 | SA-2024-29 | |
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Learning from Demonstrations | G | Benjamin Estermann | FS 24 | GA-2024-01 | |
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Puzzle solving with Graph Neural Networks | S | Joël Mathys, Benjamin Estermann |
FS 24 | SA-2024-17 | |
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The Emergence of Two-Party Systems | G | Andrei Constantinescu | FS 24 | GA-2024-02 | |
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