 Institute of Robotics and Intelligent Systems D-MAVTOpen OpportunitiesJoin our research project focused on analysing complex neurophysiological data collected during non-invasive brain stimulation experiments. This project aims to optimise brain stimulation protocols for future stroke rehabilitation by investigating neural responses to various stimulation parameters. The data includes electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmography (PPG), inertial measurement unit (IMU) readings, pupilometry, and galvanic skin response (GSR). We aim to model brain states based on these measurements to define brain circuitry outcomes from stimulation and movement interactions, using advanced techniques like connectivity-based biomarkers. This modeling will help generalise findings to broader brain states, such as valence, attention, and stress. - Applied Statistics, Biological Mathematics, Neurosciences, Simulation and Modelling
- Master Thesis
| Jellyfish-inspired robots have gained significant attention in soft robotics and biomimetic engineering due to their energy efficiency, silent propulsion, and adaptability to aquatic environments. The AI-powered Jellyfish robots offer a promising avenue for developing next-generation robotic systems with applications in biomedical research, environmental monitoring, and marine life interaction. - Engineering and Technology
- ETH Zurich (ETHZ), Master Thesis
| Ultrasound-based transcranial therapy is emerging as a non-invasive and highly precise technique for treating neurological disorders, enhancing drug delivery, and promoting brain stimulation. By leveraging an advanced ultrasound transducer array embedded in a wearable helmet, this project aims to develop a novel system for targeted, real-time brain therapy - Engineering and Technology, Medical and Health Sciences
- ETH Zurich (ETHZ), Master Thesis
| This project focuses on enhancing SLAM (Simultaneous Localization and Mapping) in operating rooms using event cameras, which outperform traditional cameras in dynamic range, motion blur, and temporal resolution. By leveraging these capabilities, the project aims to develop a robust, real-time SLAM system tailored for surgical environments, addressing challenges like high-intensity lighting and head movement-induced motion blur. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Development of a linear electrostatic film actuator for soft robotic applications such as the actuation of a humanoid robotic hand. - Electrical and Electronic Engineering, Materials Engineering, Mechanical and Industrial Engineering
- Master Thesis
| Design and build dexterous human-like robotic hands with us at the Soft Robotics Lab and the spin-off mimic. We will explore different possibilities of developing design features such as tendon-driven mechanisms, lightweight structures, and complex mechanical joints of the hand. The developed features shall be integrated into a fully functional robotic hand and applied to solve practical manipulation challenges. - Mechanical Engineering
- Bachelor Thesis, Master Thesis, Semester Project
| In this project, the student applies concepts from current advances in image generation to create artificial events from standard frames. Multiple state-of-the-art deep learning methods will be explored in the scope of this project. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| The goal of this project is to develop a shared embedding space for events and frames, enabling the training of a motor policy on simulated frames and deployment on real-world event data. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| This project focuses on the generation of detailed 3D models from a user-specified set of 3D cuboids. - Computer Vision
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| We are working on a novel product which tracks breathing with standard earphones (like Apple AirPods) only. To do this we capture the sound of breathing with the microphone which is in every earphone. We are working on an algorithm with which we can detect the ventilatory thresholds (VT1/VT2) with the breathing rate captured via the earphones. BreezeLabs is an ETH spin-off. - Biomedical Engineering, Sport and Exercise Psychology, Sports Medicine
- Internship, Master Thesis
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