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Investigate how neural rendering can become the backbone of comprehensive, next generation data-driven simulation
- Engineering and Technology, Information, Computing and Communication Sciences
- Internship, Master Thesis
| This research focuses on optimizing district thermal network design and phasing strategies by incorporating existing infrastructure and studying interplays with urban design metrics. While many existing district thermal network models often assume the absence of prior infrastructure, this study introduces methodologies to account for existing pipes, plants, and pumps, enabling a more realistic scenario for network planning. Additionally, the research explores phased implementation strategies to maximize return on investment under budget constraints, providing a pathway for incremental network construction and operation.
A key aspect of the study is the feedback loop between urban design and thermal network engineering, which quantifies how urban parameters such as building density, land use types, and development phasing affect network performance, and vice versa. The proposed methodologies are applied to case studies in Zurich, Singapore, and Shanghai, representing diverse climatic and urban contexts.
The outcomes include a framework for integrating existing infrastructure, strategies for phased implementation, and insights into the dynamic interplay between urban design and district energy systems. If time permits, the research will also produce a computational prototype for integration into the City Energy Analyst (CEA).
- Architecture, Urban Environment and Building
- Master in Integrated Building Systems (ETHZ), Master Thesis
| The reintegration of individuals who have experienced accidents is at the heart of our efforts. A severe car accident or a workplace accident can profoundly change a person's life. Such tragic events often result in serious injuries of one or multiple limbs and are classified as "polytrauma."
At our lab, we are working to mitigate the consequences of such severe accidents. Using an innovative perfusion machine, we try to keep severed limbs alive outside the body for up to four days. This time window provides the foundation for successfully retransplanting the limb to a stabilized polytrauma patient. - Biomedical Engineering, Clinical Sciences, Interfaces and Presentation
- Bachelor Thesis, Semester Project
| The objective of the project is to train a neural network taking any floorplan modality as input and outputting an embedding in a latent space shared by all the floorplan modalities. This is beneficial for downstream applications such as visual localization and model alignment. Check the attached the documents for more details.
The thesis will be co-supervised between CVG, ETH Zurich and Microsoft Spatial AI lab, Zurich. - Computer Vision
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| This project aims to develop a novel algorithm for tracking a person's health condition changes using daily life wearable sensor data, biosignals, and information from nearable sensors. With the Life-long-logging system, we want to provide meaningful data for medical staff and directly engage patients and their caregivers. - Engineering and Technology
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| The StrongAge Dataset, collected over one year, provides a rich data repository from unobtrusive, contactless technologies combined with validated mood and cognition questionnaires. This project aims to uncover digital biomarkers that can transform elderly care, addressing critical research questions related to sleep, cognition, physical activity, and environmental influences. - Biomechanical Engineering, Signal Processing
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Lab Practice, Master Thesis, Semester Project, Student Assistant / HiWi
| This project explores the use of neuroevolution for optimizing control policies in legged robots, moving away from classical gradient-based methods like PPO. Neuroevolution directly optimizes network parameters and structures, potentially offering advantages in environments with sparse rewards, while requiring fewer hyperparameters to tune. By leveraging genetic algorithms and evolutionary strategies, the project aims to develop efficient controllers for complex locomotion tasks. With computational capabilities doubling approximately every two years as predicted by Moore's Law, neuroevolution offers a promising approach for scaling intelligent control systems. - Artificial Intelligence and Signal and Image Processing
- Master Thesis
| Imagine a robot that can intelligently interpret the world from above—looking at its immediate surroundings and predict how the terrain extends beyond its sensors. If the ground beneath its feet is muddy, it might infer that the meadows ahead will have a similar challenge, adjusting its path accordingly. To enable this kind of intelligent decision-making, robots need to recognize how local conditions propagate globally.
Machine learning techniques, particularly deep learning models, offer a way to automate this understanding by clustering satellite images based on visual and structural similarities. - Intelligent Robotics
- Semester Project
| Experimental neurobiology: cognitive-behavioural investigations using touch-screen platform. This would suit a wide variety of students interested in hands on behavioural neurobiology experience. - Biology, Central Nervous System, Health, Clinical and Counselling Psychology, Mental Health, Neurocognitive Patterns and Neural Networks
- Master Thesis
| Pressure ulcers are a critical healthcare challenge, leading to increased morbidity, extended hospital stays, and higher mortality rates. These injuries, caused by sustained pressure, friction, and shear forces, affect pa-tients across all demographics, with immobilized individuals being particularly vulnerable. Neonates are at high risk due to their immature and skin, with prevalence rates in neonatal intensive care units reaching up to 28%. This project implements findings from a literature review and a clinical trial and investigates the effect of material and environmental factors on interface pressure and friction. Laboratory tests will assess the influ-ence of various mattress surface topographies and bedsheet materials in friction and compression testing us-ing state-of-the-art skin models. - Biomechanical Engineering
- Internship, Lab Practice, Master Thesis, Semester Project
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