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The goal of the project is to develop metal oxide-based logic electronics, for use in rectification and/or memristor application. - Biomedical Engineering, Electrical and Electronic Engineering, Materials Engineering
- Bachelor Thesis, Master Thesis, Semester Project
| The interaction between natural snowfalls and atmospheric wind conditions can lead to complex snow clustering dynamics mediated by turbulence. For example, the formations of columnar structures and kinematic waves such as those present in particle-laden flows. How do such complex systems composed of millions of snowflakes lead to structure in the presence of a large variety of atmospheric turbulence conditions? Which kind of structures form depending on the snow mass loading, the type of frozen hydrometeor, and the atmospheric turbulence intensity levels? Building on a previous project that performed planar imaging, this project will focus on performing volumetric field imaging. Measurements will be performed at a professional field site in Davos where a holography setup will collocate snowflake characterization. To process the imaging data the student will join forces at the DLR in Göttingen and track snowflakes using state-of-the-art ‘Shake-the-Box’ Lagrangian particle tracking methodology. - Aerospace Engineering, Earth Sciences, Environmental Engineering, Mathematical Sciences, Mechanical Engineering, Physics
- ETH Zurich (ETHZ), Master Thesis
| This project aims to develop a compact wireless device designed to monitor the electrical activity of cardiac tissues. The device will incorporate advanced PCB design, a low-noise amplifier, a transceiver, and efficient power management systems. - Integrated Circuits
- Master Thesis, Semester Project
| Tree species maps are crucial for effective forest management, biomass assessment, and biodiversity monitoring. Remote sensing products offer flexible and cost-effective ways to assess forest characteristics, while deep learning methods promise high predictive accuracy and transformative applications in forestry. This study aims to apply novel deep learning approaches to detect and identify individual trees and tree species in mixed forests. By addressing the challenges of tree species identification, this research will enhance biodiversity assessment, forest resilience understanding, and management strategies. - Artificial Intelligence and Signal and Image Processing, Forestry Sciences, Geomatic Engineering
- ETH Zurich (ETHZ), Master Thesis
| The project aims to create a controller for an interesting and challenging type of quadrotor, where the rotors are connected via flexible joints. - Control Engineering, Flight Control Systems, Intelligent Robotics, Systems Theory and Control
- Master Thesis, Semester Project
| Fracture surfaces in rock cores contain valuable structural information crucial for geological interpretation, engineering design, and are commonly mapped and analyzed by geologists. With advancements in camera technologies and computational techniques, it is now possible to digitize these surfaces in high resolution and apply automated methods for fracture analysis. - Computer Vision, Geology, Image Processing, Photogrammetry and Remote Sensing
- Bachelor Thesis, Master Thesis, Semester Project
| This project aims to use vision-based world models as a basis for model-based reinforcement learning, aiming to achieve a generalizable approach for drone navigation. - Computer Vision, Intelligent Robotics, Simulation and Modelling
- Master Thesis, Semester Project
| We aim to learn vision-based policies in the real world using state-of-the-art model-based reinforcement learning. - Computer Vision, Flight Control Systems, Intelligent Robotics
- Master Thesis, Semester Project
| Do you feel more in the mood to book a ski weekend on a sunny Monday or a rainy Monday? Our decisions can be influenced by many factors—including the environment around us. This study explores how non-social environmental factors, such as current and past weather and temperature, influence economic decision-making, including risk-taking, choice consistency, and rationality. We aim to develop a data analysis pipeline for processing large datasets with multiple features, using machine learning techniques like lasso and ridge regression to identify key predictors of economic behavior. The project involves parameter tuning, assumption checking, and feature selection to ensure robust, interpretable models. If time permits, weather data will be scraped from the web based on geolocation to further enhance the analysis of environmental conditions. By investigating how these contextual factors shape economic decisions, we aim to provide insights into the dynamic forces influencing individual choices, challenging the view of economic preferences as stable dispositions. - Behavioural and Cognitive Sciences, Economics
- Master Thesis, Semester Project
| The proliferation of mobile and embedded devices has spurred the demand for efficient, high-quality
speech synthesis systems that operate entirely on-device. This project aims to develop a fast,
quantized speech synthesis pipeline optimized for mobile platforms (i.e. Samsung Galaxy, Google
Pixel Pro 8), focusing on reducing computational load and memory usage without compromising
audio quality. - Engineering and Technology, Information, Computing and Communication Sciences
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
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