 |
|
|||
Current Theses for all TIK GroupsB = Bachelor, G = Group, M = Master, S = Semester |
||||||||
| title | category | type | contact/supervisor | assigned | student(s) | thesis number | edit | |
|---|---|---|---|---|---|---|---|---|
 |
Algorithmic Reasoning with Graph Neural Networks | B | Florian Grötschla, Joël Mathys |
FS 24 | BA-2024-03 |   |
||
 |
Anomaly and vulnerability detection for smart contracts | M | Benjamin Estermann, Ye Wang |
FS 24 | MA-2024-13 | |
||
 |
Benchmarking Pretrained EEG Models | B | Ard Kastrati | FS 24 | BA-2024-10 | |
||
 |
Breaking Google’s reCAPTCHAv3 | S | Andreas Plesner | FS 24 | SA-2024-09 | |
||
 |
Breaking Google’s reCAPTCHAv3 - Getting good cokkies | S | Andreas Plesner | FS 24 | SA-2024-11 | |
||
 |
Breaking Google’s reCAPTCHAv3 - How are humans classified | S | Andreas Plesner | FS 24 | SA-2024-10 | |
||
 |
CLAPv2 | M | Luca Lanzendörfer, Florian Grötschla |
FS 24 | MA-2024-12 | |
||
 |
Compute-Efficient Pretraining of Large EEG Models | B | Ard Kastrati | FS 24 | BA-2024-09 | |
||
 |
Conditional Generation of Wavetables | B | Luca Lanzendörfer, Florian Grötschla |
FS 24 | BA-2024-07 | |
||
| Data driven anomaly detection for rails using in service railway vehicles | B | Andreas Plesner | FS 24 | BA-2024-02 | |
|||
 |
Data driven anomaly detection of springs in in-service railway vehicles | B | Andreas Plesner | FS 24 | BA-2024-06 | |
||
 |
Decoding Energy Market Deviations: An Autoencoder-Based Framework for Transnational Anomaly Prediction | M | Benjamin Estermann | FS 24 | MA-2024-01 | |
||
 |
Distributed Stable Matchings | M | Diana Ghinea, Andrei Constantinescu |
FS 24 | MA-2024-11 | |
||
 |
Evaluating Audio Metrics | S | Luca Lanzendörfer, Florian Grötschla |
FS 24 | SA-2024-06 | |
||
 |
Evaluating Positional Encodings for Graph Transformers | S | Florian Grötschla | FS 24 | SA-2024-02 | |
||
|
Finding sybils using GNNs | M | Andreas Plesner | FS 24 | MA-2024-08 | |
||
 |
Game Theory for Games: Algorithms and Axioms | G | Andrei Constantinescu | FS 24 | GA-2024-03 | |
||
 |
GNNs for Supply Chain Networks | S | Florian Grötschla, Joël Mathys |
FS 24 | SA-2024-16 | |
||
 |
Graph Algorithms for Dynamic Directories | M | Andrei Constantinescu, Pankaj Khanchandani |
FS 24 | MA-2024-15 | |
||
 |
Graph Neural Networks on Music Graphs | S | Florian Grötschla, Luca Lanzendörfer |
FS 24 | SA-2024-01 | |
||
 |
Hierarchical Graph Transformers | S | Florian Grötschla | FS 24 | SA-2024-03 | |
||
 |
Immitating Byzantine Behavior in Distributed Systems | M | Yann Vonlanthen | FS 24 | MA-2024-16 | |
||
 |
Incentivizing Simple Transactions | B | Lioba Heimbach, Andrei Constantinescu |
FS 24 | BA-2024-01 | |
||
 |
Jigsaw puzzle solver using machine learning | S | Andreas Plesner, Till Aczél |
FS 24 | SA-2024-04 | |
||
 |
Learning Finite State Automatons on Graphs with Reinforcement Learning | M | Florian Grötschla, Joël Mathys |
FS 24 | MA-2024-04 | |
||
 |
Learning from Demonstrations | G | Benjamin Estermann | FS 24 | GA-2024-01 | |
||
 |
Lightning Network + GNNs | M | Florian Grötschla, Lioba Heimbach |
FS 24 | MA-2024-07 | |
||
 |
Liquid Staking Token Risks | B | Lioba Heimbach, Robin Fritsch |
FS 24 | BA-2024-08 | |
||
 |
Lyrics Alignment | S | Luca Lanzendörfer, Florian Grötschla |
FS 24 | SA-2024-12 | |
||
 |
Lyrics-to-Vocals | M | Luca Lanzendörfer, Florian Grötschla |
FS 24 | MA-2024-06 | |
||
 |
Mel Spectrogram Vocoder | S | Luca Lanzendörfer, Florian Grötschla |
FS 24 | SA-2024-07 | |
||
 |
Neural Implicit Representations | M | Luca Lanzendörfer, Benjamin Estermann |
FS 24 | MA-2024-05 | |
||
|
Neural Walk-on-Sphere for Poisson Equation | M | Roger Wattenhofer | FS 24 | MA-2024-10 | |
||
 |
open-source Llark | B | Luca Lanzendörfer, Florian Grötschla |
FS 24 | BA-2024-05 | |
||
|
Optimal Routing for 2D Mesh-based Analog Compute-In-Memory Accelerator Architecture | M | Roger Wattenhofer | FS 24 | MA-2024-09 | |
||
 |
Puzzle solving with Graph Neural Networks | S | Joël Mathys, Benjamin Estermann |
FS 24 | SA-2024-17 | |
||
 |
Recommender Systems for Politics | M | Yann Vonlanthen, Frédéric Berdoz |
FS 24 | MA-2024-03 | |
||
 |
Reconstructing ODEs for railway vehicles using ML | B | Andreas Plesner | FS 24 | BA-2024-04 | |
||
 |
State Replication on Demand | M | Yann Vonlanthen, Quentin Kniep |
FS 24 | MA-2024-02 | |
||
 |
Stock Market Graphs | S | Florian Grötschla, Joël Mathys |
FS 24 |
, |
SA-2024-13 | |
|
|
Structured Sparsity for Efficient Model Inference | S | Peter Belcák | FS 24 | SA-2024-14 | |
||
 |
Text-to-Speech Arena | S | Luca Lanzendörfer, Florian Grötschla |
FS 24 | SA-2024-05 | |
||
 |
The Emergence of Two-Party Systems | G | Andrei Constantinescu | FS 24 | GA-2024-02 | |
||
 |
Using PINNs to predict rail irregularities | M | Andreas Plesner | FS 24 | MA-2024-14 | |
||
 |
Building a Multi-Cryptocurrency Node Explorer Webpage | Peer-to-Peer Networks | S | Lucianna Kiffer | FS 24 | SA-2024-08 | |
|
 |
Deep Dive Into Peer Discovery | Peer-to-Peer Networks | M | Lucianna Kiffer, Yann Vonlanthen |
FS 24 | MA-2024-17 | |
|
 |
Infrastructure Impact of Cryptocurrency Networks | Peer-to-Peer Networks | S | Lucianna Kiffer | FS 24 | SA-2024-15 | |
|
|
Automated Electronic Placement and Routing | M | Florian Grötschla, Benjamin Estermann |
HS 23 | MA-2023-14 | |
||
 |
Best pokemon team | B | Andreas Plesner | HS 23 | BA-2023-23 | |
||
 |
Bring Your Own Idea: Music Dataset | B | Luca Lanzendörfer, Florian Grötschla |
HS 23 | BA-2023-20 | |
||
 |
Calling all Game Devs: WikiWalker | G | Luca Lanzendörfer | HS 23 |
, , , |
GA-2023-10 | |
|
 |
Characterization of the Ethereum Workload | M | Lioba Heimbach, Quentin Kniep |
HS 23 | MA-2023-23 | |
||
|
Contrastive Learning and Predictability Minimization Continued | S | Béni Egressy | HS 23 | SA-2023-29 | |
||
|
Decentralized Learning with GNNs | M | Béni Egressy | HS 23 | MA-2023-24 | |
||
 |
Deep Learning Models for Decoding Brain Activity | B | Ard Kastrati | HS 23 | BA-2023-21 | |
||
|
Deep Learning Models for Decoding Brain Activity | S | Ard Kastrati | HS 23 | SA-2023-34 | |
||
|
Dense Representations for Efficient Language Modelling | M | Peter Belcák | HS 23 | MA-2023-20 | |
||
|
Extending the CUSF library - Airy functions | B | Andreas Plesner | HS 23 | BA-2023-22 | |
||
 |
Fairness and Proportionality in Allocation of Indivisible Goods | M | Andrei Constantinescu | HS 23 | MA-2023-03 | |
||
 |
GNN Pretraining | M | Béni Egressy | HS 23 | MA-2023-21 | |
||
 |
Swarm Intelligence Reinforcement Learning | M | Benjamin Estermann, Florian Grötschla |
HS 23 | MA-2023-15 | |
||
|
Text Compression for Efficient NLP | M | Peter Belcák | HS 23 | MA-2023-19 | |
||
 |
Attacking the Network Layer of Ethereum | Peer-to-Peer Networks | M | Lucianna Kiffer, Yann Vonlanthen |
HS 23 | MA-2023-13 | |
|
