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To enable new applications on drone platforms, novel sensors coupled with with machine learning algorithms are essential. Such sensors are, for example, event-based cameras. They are fast (~kHz speed) and resilient to the environment (e.g. poor lighting conditions). Current cameras already utilize small FPGAs to convert the event stream to common interface standards, such as USB. However, for our drone system already incorporates a powerful FPGA for processing, these conversions waste energy and increase processing latency. - Electrical and Electronic Engineering
- Drones (PBL), FPGA (PBL), Neuromorphic (PBL), PCB Design (PBL), Semester Project
| Polymer networks are made by cross-linking polymer chains at their ends by means of a chemical reaction. While the properties of used reactions are usually very well characterized for small molecules, little is known about how the presence of a polymer chain and its length affect this reaction. In this project, we aim to study this, mostly experimentally, but also including a theoretical approach. We propose to start with boronic ester chemistry, which has been already characterized in literature and in our lab. the reactants will be functionalized on linear PEG chains. We plan on studying both the thermodynamic and kinetic parameters. - Characterisation of Macromolecules, Physical Chemistry of Macromolecules, Thermodynamics and Statistical Physics
- Bachelor Thesis, Master Thesis, Semester Project
| To enable new applications on drone platforms, novel sensors coupled with with machine learning algorithms are essential. Such sensors are, for example, event-based cameras. They are fast (~kHz speed) and resilient to the environment (e.g. poor lighting conditions). To utilize the full potential of these cameras, neuromorphic computing is needed to process their output. Our FPGA-based drone platform is capable of operating such an event-based camera, and allows for efficient hardware acceleration of the computationally expensive neuromorphic algorithms. - Electrical and Electronic Engineering
- Drones (PBL), FPGA (PBL), Master Thesis, Neuromorphic (PBL), Software (PBL)
| Bruxism is characterized by tooth grinding and jaw clenching that severely affects around 8% of the popu-
lation. It can take place either during sleep (sleep bruxism) or during wakefulness (awake bruxism). Developments in
mobile computing and micro electronics allows for the continuous monitoring in real-world environments. Real-world
monitoring prompts the need to correctly classify the recorded signals. In the lab, we are interested in developing a
classification method to distinguish between sounds of bruxism (tooth grinding and jaw clenching), eating, reading,
talking, and drinking. - Engineering and Technology
- Master Thesis
| Bruxism is characterized by tooth grinding and jaw clenching that severely affects around 8% of the popu-
lation. It can take place either during sleep (sleep bruxism) or during wakefulness (awake bruxism). With the recent
development in mobile computing and micro electronics, the applicability of wearable sensors has improved rapidly.
According to the literature, the ear presents itself as a promising candidate for biosensing because it gives access to
multiple biomarkers such as the core body temperature, heart rate, and the breathing rate. In addition, an ear-worn
device is socially tolerable and convenient making it comfortable to be used for a prolonged period without affect-
ing the user’s daily routine. In the lab, we are interested in developing a wearable device to monitor sounds of Bruxism. - Engineering and Technology
- Master Thesis
| Bone exhibits a remarkable ability to adapt its microstructure in response to mechanical and metabolic demands. This process involves a dynamic balance between bone-forming osteoblasts and bone-resorbing osteoclasts, with osteocytes playing a crucial role in signaling micro-mechanical cues. Disruptions in these mechanisms, as seen in conditions like postmenopausal osteoporosis, lead to decreased bone density and increased fracture risk. Sclerostin is pivotal in determining bone formation or resorption in response to mechanical stimuli and is targeted by FDA-approved osteoporosis medications. However, the drug's mechanism and its interaction with mechanical loading remain unclear. This project aims to investigate bone's response to sclerostin antibody treatment and uncover the cellular mechanisms governing bone adaptation using single-cell mechanomics cluster analysis. - Computational Biology and Bioinformatics, Engineering and Technology, Mathematical Sciences, Medical and Health Sciences, Physics
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| In continual learning, deep learning models incrementally learn more classes or tasks over time. Doing so, they should not forget previously learned knowledge. This is a hard and active research problem. Making it even harder, we want the models to also estimate correct uncertainty. E.g., they should be highly uncertain about a new object type, but not uncertain about an object that they just learned correctly.
[1] Parisi et al., Lifelong learning with neural networks http://dx.doi.org/10.1016/j.neunet.2019.01.012
[2] Gawlikowski et al., Uncertainty in Deep Neural Networks http://arxiv.org/abs/2107.03342 - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Rotation optimization occurs in camera calibration, kinematics, animation, and attitude setting of spacecraft. These optimization problems are generically nonconvex and difficult to solve, but some problem variations offer exact solutions in the low-noise and outlier-free setting. This project will investigate Harmonic Hierarchies of polynomials as a mechanism to perform global optimization of outlier-robust rotation alignment tasks. Harmonic Hierarchies utilize the properties of the rotation space and binary hypercube to produce a sequence of linear programs in increasing size, yielding a sequence of convergent upper-bounds and lower-bounds to the true alignment error. Extensions to this project can include multi-camera alignment (group averaging) and problems in inverse kinematics.
This project will be performed in collaboration with Lucas Slot (ETH Zurich: D-MATH) and Mauricio Velasco (Universidad Catolica del Uruguay). - Engineering and Technology, Mathematics
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| In this project, co-supervised by Swissgrid, we will look into the problem of designing incentives for the procurement of voltage support services in the grid. The design of an efficient mechanism requires the use of tools from control theory, game theory, and optimization. - Electrical Engineering
- Collaboration, Energy (IfA), Master Thesis
| For image and video and novel sensors, such as event-based vision processing, projects often make use open source libraries (e.g. OpenCV) for image processing on CPUs and GPUs, enabling fast prototyping and proof of concepts. However, drone platforms require algorithms to execute as efficient as possible. This allows less weight and energy consumption of the computing element, enabling longer flight duration or higher payload. FPGAs offer a promising approach, however, video processing algorithms are typically executed on hand-crafted hardware accelerators. To leverage the open source algorithms and libraries, efficient conversion from C and C++ to HDL accelerators is needed. - Electrical and Electronic Engineering
- FPGA (PBL), Master Thesis
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