Department of Computer ScienceAcronym | D-INFK | Homepage | http://www.inf.ethz.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Parent organization | ETH Zurich | Current organization | Department of Computer Science | Child organizations | |
Open OpportunitiesMotivation: Explore the newly improved Habitat 3.0 simulator with a special focus on the Virtual Reality Features.
This project is meant to be an exploration task on the Habitat 3.0 simulator, exploring all the newly introduced features focusing specifically on the implementation of virtual reality tools for scene navigation. The idea is to extend these features to self created environments in Unreal Engine that build uppon Habitat - Artificial Intelligence and Signal and Image Processing
- Semester Project
| Motivation: Create a realistic rendered benchmark to evaluate reinforcement agents, visual navigation tasks, interaction with other agents, navigation in scene with static and dynamic objects and humans.
How: Create a realistic rendered benchmark to evaluate reinforcement agents, visual navigation tasks, interaction with other agents, navigation in scene with static and dynamic objects and humans. - Artificial Intelligence and Signal and Image Processing
- Master Thesis
| This project seeks to advance the field of legged robotics by creating a versatile and accessible co-design framework that integrates mechanical design and control optimization. - CAD/CAM Systems, Computer Graphics, Dynamical Systems, Intelligent Robotics, Mechanical and Industrial Engineering, Operations Research, Optimisation, Robotics and Mechatronics
- Master Thesis, Semester Project
| This Master’s thesis proposal, beginning in February 2025, aims to develop a non-invasive AI algorithm to estimate low-voltage areas (LVAs) in atrial fibrillation (AF) patients. Identifying LVAs, typically done through invasive intracardiac mapping, is crucial for tailoring ablation strategies. By combining 12-lead ECGs, clinical data, and imaging features, the proposed model seeks to localize LVAs, supporting personalized treatment and minimizing the need for invasive mapping. Advanced techniques such as variational inference, diffusion models, and transformers will be explored to enhance AF management and patient outcomes. - Arithmetic and Logic Structures, Biomedical Engineering, Computer Vision, Electrical and Electronic Engineering, Knowledge Representation and Machine Learning
- ETH Zurich (ETHZ), Master Thesis
| 30 June - 29 August 2025. The fellowship provided by the Computer Science Department of ETH takes place during two summer months and is open to all students worldwide. The department is committed to increasing diversity in the computer science area. - Information, Computing and Communication Sciences
- ETH SSR Fellowship Program (ETHZ), Internship, Lab Practice
| The project investigates the application of pre-trained large language models (LLMs) and vision-language models (VLMs) to human motion analysis tasks, including motion prediction, generation, and denoising. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| This project aims to transform the way users engage with data in spreadsheets by creating an interactive, collaborative platform for data storytelling. The motivation is to make data analysis more engaging, accessible, and narrative-driven, allowing users to seamlessly weave stories around their data while leveraging the power of large language models (LLMs). The platform will feature a community-based web forum where users can access a variety of public datasets or upload their own. Each dataset can be imported into a storytelling system integrated within the spreadsheet environment. This system will allow users to perform common data operations, such as calculating averages, standard deviations, and generating visualizations (e.g., charts), while the LLM will offer suggestions for a cohesive narrative. For instance, the system can auto-generate explanatory text based on the user’s data manipulations, creating a comprehensive story of the dataset. The goal is to help users articulate insights, uncover trends, and communicate findings in a more structured and compelling way. (Target Venue: ACM UIST 2025)
- Interdisciplinary Engineering
- ETH Zurich (ETHZ), Master Thesis
| This project seeks to raise awareness among young people about the presence and influence of algorithmic bias in social media apps. Youth often interact with these platforms without fully understanding how their interactions contribute to biased content curation. To address this, we propose the development of a web-based system that simulates a social media app, providing real-time feedback on how user-generated content can influence algorithmic bias. The web system will function as a mock social media platform where users, particularly young people, can post content as they would on real social media apps. When users submit posts, the system will generate a preview that shows how the content spreads through the platform. This preview will visually represent how the content engages with algorithms, potentially amplifying biases based on factors like language, content type, or context. By seeing this in action, users will learn how their posts can unintentionally reinforce algorithmic bias, encouraging them to be more mindful of their contributions. (Target Venue: ACM UIST 2025)
- Interdisciplinary Engineering
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis
| In this project, we aim to develop a visualization tool designed for rendering and interacting with 3D human motion and scenes. - Computer Graphics, Computer Software, Computer Vision, Engineering and Technology, Virtual Reality and Related Simulation
- Bachelor Thesis, Semester Project
| In this semester thesis, our goal is to enable an F1Tenth car, an autonomous vehicle at 1:10 scale of a Formula 1 car, to accurately detect its designated driving lane using RGB-D images captured by an onboard camera. - Computer Vision, Intelligent Robotics
- Semester Project
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