Department of Information Technology and Electrical EngineeringAcronym | D-ITET | Homepage | http://www.ee.ethz.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Parent organization | ETH Zurich | Current organization | Department of Information Technology and Electrical Engineering | Child organizations | |
Open OpportunitiesDevelopment of a software tool which visualises the geometry of a basic switching cell based on geometrical parameters derived by converter optimisation procedures - Electrical Engineering
- Master Thesis, Semester Project
| Development of switching cell mechanical models in the X3D format based on geometrical parameters derived by converter optimisation procedures - Electrical Engineering
- Master Thesis, Semester Project
| In this thesis the student is provided the opportunity to optimize and build a medium frequency transformer - Electrical and Electronic Engineering
- Master Thesis, Semester Project
| In this thesis the student will investigate different methods to measure the partial discharge inception of transformer winding geometries. - Electrical Engineering
- Master Thesis
| This project aims to revolutionize the analysis of electroencephalography (EEG) data by developing a specialized foundational model utilizing the principles of artificial intelligence. Despite the critical role of EEG in diagnosing and treating neurological disorders, challenges such as low signal-to-noise ratios and complex signal patterns hinder practical analysis. By adapting strategies from successful domains like natural language processing and computer vision, this project will build a machine learning model tailored for EEG signals. The model will undergo extensive pre-training on diverse EEG datasets to establish a robust understanding of neural activities, followed by fine-tuning for specific clinical tasks such as seizure detection and sleep stage classification. Our approach promises to enhance the accuracy, efficiency, and accessibility of EEG diagnostics, paving the way for improved patient outcomes. Validation and testing using standard performance metrics will measure the model's efficacy, setting a new standard in EEG analysis. - Electrical Engineering, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition, Signal Processing, Simulation and Modelling
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| The aim of the project is to develop a deep learning model capable of performing 3D semantic segmentation of the different features of the middle ear, from synchrotron-based X-ray microtomography 3D volumes. Challenges include developing a high-performance algorithm for handling large data sizes (20 GB per volume). The project consists in a first phase about dataset generation followed by a second phase of development/selection of the most appropriate DL model and metrics. - Computer Vision, Image Processing, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Otorhinolaryngology
- Collaboration, Master Thesis, Semester Project
| Open vocabulary video semantic segmentation (OV-VSS) aims to assign a semantic label to each pixel of each frame of the video given an arbitrary set of open-vocabulary category names. There are a number of attempts on open vocabulary image semantic segmentation (OV-ISS). However, OV-VSS does not get enough attention due to the difficulty of video understanding tasks in modeling local redundancy and global correlation. In this master thesis project, we plan to fill the gap by extending existing OV-ISS methods to OV-VSS. Specifically, we aim to develop a OV-VSS method which achieves high accuracy by using temporal information and keeps high efficiency.
- Artificial Intelligence and Signal and Image Processing
- Master Thesis
| This project aims at developing a machine learning approach (for example, using convolutional neural networks) for localizing and tracking anatomical landmarks from cardiac MR images. - Biomedical Engineering, Electrical and Electronic Engineering
- Master Thesis
| Sum-of-Squares (SOS) relaxation is a beautiful technique to solve nonconvex optimization problems. As computational capabilities continue to increase, so is the scope of engineering challenges that can be tackled with this method. The goal of this project is to exploit the flexibility of SOS relaxations to design new data-driven control methods for linear dynamics, that can more efficiently incorporate prior knowledge on the system and cope with noisy input-output data. - Dynamical Systems, Optimisation, Systems Theory and Control
- Applications (IfA), Computation (IfA), Master Thesis, Theory (IfA)
| About 8inks:
Lithium-ion batteries have revolutionized the world we live in today by enabling applications in mobile electronics
ranging from laptops, smart phones, to smart watches. Today, electrification of large industries such as electric
passenger vehicles, trucks, grid energy storage, and aviation is inhibited as conventional lithium-ion batteries
approach the limits of their performance. NextGen batteries are considered to bring the required performance
improvements but lack a low-cost, scalable manufacturing solution for market breakthrough.
At eightinks, we develop a revolutionary manufacturing solution of NextGen batteries: multilayer curtain coating. Our
technology allows high battery energy density, charging speed, and safety, all combined with lower production costs. It
is material agnostic and can serve as a platform solution for various segments of the battery market. To develop our
technology to the earliest possible market entry, we are working on all relevant aspects of NextGen battery design,
production, assembly, and testing. - Engineering and Technology
- Internship, Student Assistant / HiWi
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