Theses & Semester Projects
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How to apply:
- Please review the available projects below
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Modeling and Control of an Ex-Vivo Perfusion Machine
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, such as severed 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.
Keywords
Mathematical modeling; Control; Biomedical; Optimization; Fluiddynamics
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-03-28 , Earliest start: 2025-04-01 , Latest end: 2025-12-23
Applications limited to ETH Zurich
Organization Research Onder
Hosts Neumann Marc-Philippe
Topics Engineering and Technology
Differential Particle Simulation for Robotics
This project focuses on applying differential particle-based simulation to address challenges in simulating real-world robotic tasks involving interactions with fluids, granular materials, and soft objects. Leveraging the differentiability of simulations, the project aims to enhance simulation accuracy with limited real-world data and explore learning robotic control using first-order gradient information.
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Semester Project , Master Thesis
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Published since: 2025-03-10 , Earliest start: 2025-01-01 , Latest end: 2025-12-31
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization Robotic Systems Lab
Hosts Nan Fang , Ma Hao
Topics Engineering and Technology
Performance and sustainability assessment of an EV traction system
Design new control strategies to maximize efficiency as well as lifetime in BEVs.
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Semester Project , Master Thesis
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Published since: 2025-03-10 , Earliest start: 2025-01-01 , Latest end: 2025-12-01
Organization Research Frazzoli
Hosts Censi Andrea
Topics Engineering and Technology
Infrastructure Optimization for Bus Fleet Electrification
Development of an open-source Python toolbox for optimizing electric bus fleet electrification in Switzerland, focusing on charging infrastructure, battery sizing, and strategy. The next phase aims to enhance compatibility, expand charging options, integrate new energy sources, and improve computational efficiency in collaboration with PostAuto.
Keywords
Electric bus, fleet electrification, charging infrastructure, Dynamic programming
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Master Thesis
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Published since: 2025-02-19
Organization Research Onder
Hosts Moradi Mohammad
Topics Engineering and Technology
Efficient Sampling-based GP-MPC for autonomous robots
Most control methods operate under the assumption of a known model. However, in practice, knowing the exact dynamics model a priori is unrealistic. A common approach is to model the unknown dynamics using Gaussian Processes (GPs) which can characterize uncertainty and formulate a Model Predictive Control (MPC) type problem. However, it is difficult to exactly utilize this uncertainty characterization in predictive control. In a recent approach [1], we proposed a sampling-based robust GP-MPC formulation for accurate uncertainty propagation by sampling continuous functions. In contrast, in the proposed project, you will implement an approximation method for sampling continuous functions using a finite number of basis functions [2] and solve the MPC problem jointly with the sampled dynamics. You will analyze the trade-offs between performance, approximation accuracy, and computational cost for this method.
Keywords
Gaussian Processes, model predictive control (MPC), Issac sim simulator, uncertainty propagation, Algorithms
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Semester Project , Master Thesis
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Published since: 2025-02-14 , Earliest start: 2025-02-16 , Latest end: 2025-10-31
Organization Research Zeilinger
Hosts Prajapat Manish
Topics Engineering and Technology
Strategic Interactions of Future Mobility Systems
Mobility is typically self-optimized for a particular region to accommodate internal travel needs. However, as soon as one considers multiple, interacting regions (e.g., urban areas interacting with agglomerations, and agglomerations interacting with rural areas), important coordination issues occur, including scheduling mismatches, fleet allocations, and congestion peaks. In short, a mobility system composed of self-optimized mobility systems seems to often operate suboptimally. In this project, we will investigate the idea of strategic interactions of future mobility stakeholders across heterogeneous regions, such as urban areas, agglomerations, and rural areas, leveraging techniques from network design, optimization, game theory, and policy making.
Keywords
Optimization, Game theory, Multi-agent interactions, Transportation systems, Robotics
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Semester Project , Master Thesis
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Published since: 2025-02-07 , Earliest start: 2024-11-10 , Latest end: 2025-12-31
Applications limited to ETH Zurich
Organization Research Frazzoli
Hosts He Mingjia
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Vision-based Autonomous Racing with F1Tenth Car
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 race safely on a track that is perceived through RGB-D images captured by an onboard camera.
Keywords
vision-based control, autonomous racing, image processing
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Semester Project
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Published since: 2025-01-31 , Earliest start: 2025-01-15
Organization Research Zeilinger
Hosts Trisovic Jelena
Topics Engineering and Technology
Robust predictive control for safe and optimal control of nonlinear uncertain systems
This project aims to improve the design of predictive controllers that robustly ensure safe operation for a large class of uncertain nonlinear systems.
Keywords
Model predictive control, robust control, nonlinear systems, learning-based control
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-01-27
Organization Research Zeilinger
Hosts Köhler Johannes
Topics Mathematical Sciences
Teaching a robot to master a board game using Reinforcement Learning
Updated Project Description Our research project explores how physical robots can learn to play board games via Reinforcement Learning (RL). We currently employ OpenAI Gym environments with Stable Baselines3 to train an agent directly on our 2D gantry robot hardware integrated with ROS2. In parallel, we leverage NVIDIA’s Isaac Gym for a high-fidelity simulation environment, which allows us to iterate on policies before transferring them to the real robot. A key focus of the project is bridging the sim-to-real gap and reducing the time required for on-hardware training using sophisticated RL techniques. We explore multiple RL approaches—both in simulation and on physical hardware—to investigate robust policy learning strategies. RTX 4090 GPUs back these trainings. The project offers a unique opportunity to design, refine, and deploy RL algorithms in a real-world setting. We seek students to help improve our existing software and hardware pipelines by experimenting with various RL methods. The ultimate goal is to enable the robot to excel at board games against human opponents and other learned agents, showcasing advanced capabilities in real-world reinforcement learning.
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Semester Project , Master Thesis
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Published since: 2025-01-27 , Earliest start: 2024-08-15
Organization Research D'Andrea
Hosts Ramachandran Aswin
Topics Engineering and Technology
AI-Supported Energy Management Optimization for Hybrid Ships
This thesis explores advanced energy management for hybrid ships using Dynamic Programming (DP) and Model Predictive Control (MPC). It integrates Long Short-Term Memory (LSTM) models aiming to improve load forecasting, energy demand prediction, and operational optimization, with a focus on real-world constraints and maritime applications.
Keywords
Machine learning, Hybrid Ships, Hybrid vessels, Energy Management Systems, Dynamic Programming (DP), Model Predictive Control (MPC), Long Short-Term Memory (LSTM)
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Master Thesis
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Published since: 2025-01-20 , Earliest start: 2025-01-20
Organization Research Onder
Hosts Moradi Mohammad
Topics Engineering and Technology
Hardware-in-the-Loop Testing of Cerebrospinal Fluid Shunt Systems for Hydrocephalus Patients
Hydrocephalus is a medical condition characterized by the disturbed dynamics of cerebrospinal fluid (CSF) and its excessive accumulation in the brain ventricles. In contemporary therapy, a shunt system is implanted that drains CSF from the ventricles into the peritoneal space. While various types of shunt systems exist, they are essentially all based on passive mechanical pressure valves that are driven by the external pressure gradient. This limits the efficacy of these shunts and complications such as over- and underdrainage may occur. To improve the therapy of hydrocephalus, we are working towards intelligent mechatronic shunt systems that are capable of monitoring vital signs and adapting CSF drainage according to the patient’s actual needs. In this project, you will support the technical upgrade of an existing hardware-in-the-loop test bench that is used for the evaluation of existing shunt systems and the development of smart shunt system.
Keywords
Estimation and Control, Mechatronic Systems
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Student Assistant / HiWi
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Published since: 2025-01-14 , Earliest start: 2025-01-15
Applications limited to ETH Zurich
Organization Research Zeilinger
Hosts Flürenbrock Fabian
Topics Mathematical Sciences , Engineering and Technology
Online Learning of Dynamic Control for Soft Manipulators
This project aims to develop an online learning framework for achieving precise position control of a soft robotic arm while adapting to time-varying system dynamics.
Keywords
online learning, distribution shift, soft robotics, position control
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Master Thesis
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Published since: 2025-01-08 , Earliest start: 2024-11-07 , Latest end: 2025-08-01
Organization Research Zeilinger
Hosts Ma Hao
Topics Engineering and Technology
Digital Twin for Spot's Home
MOTIVATION ⇾ Creating a digital twin of the robot's environment is crucial for several reasons: 1. Simulate Different Robots: Test various robots in a virtual environment, saving time and resources. 2. Accurate Evaluation: Precisely assess robot interactions and performance. 3. Enhanced Flexibility: Easily modify scenarios to develop robust systems. 4. Cost Efficiency: Reduce costs by identifying issues in virtual simulations. 5. Scalability: Replicate multiple environments for comprehensive testing. PROPOSAL We propose to create a digital twin of our Semantic environment, designed in your preferred graphics Platform to be able to simulate Reinforcement Learning agents in the digital environment, to create a unified evaluation platform for robotic tasks.
Keywords
Digital Twin, Robotics
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Semester Project , Master Thesis
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Published since: 2024-12-17 , Earliest start: 2025-01-05
Applications limited to University of Zurich , ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization Computer Vision and Geometry Group
Hosts Blum Hermann , Portela Tifanny , Bauer Zuria, Dr. , Trisovic Jelena
Topics Information, Computing and Communication Sciences
Design a Storytelling Map for Transport Network Design in Multi-regions
Transport networks in neighboring regions are interconnected, meaning that for interregional trips, the utilization of transport services is influenced by both networks rather than a single one. We propose a cooperative transport planning framework, highlighting the benefits of co-investment and payoff sharing. To effectively engage decision-makers, it is crucial to analyze cooperative strategies and demonstrate the impact of negotiations using advanced visualization techniques. In this project, we want to design and develop an interactive storytelling map that can help explain the impact of cooperation on environmental sustainability, transport affordability, and public transport profitability. The storytelling map will explain the background, visualize the different transportation network plans, and further show the impact on transportation operators and passengers.
Keywords
Storytelling Map, User-friendly web-based application, Graphic user interface design, Transport Network.
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Semester Project , Internship
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Published since: 2024-12-16 , Earliest start: 2025-02-01 , Latest end: 2025-05-31
Organization Research Frazzoli
Hosts Zuo Chenyu, Dr , He Mingjia
Topics Information, Computing and Communication Sciences , Engineering and Technology
Monitoring and prediction for neuro-intensive care
Delayed cerebral ischemia (DCI) occurs in up to one third of patients with treated aneurysmal subarachnoid hemorrhage. Due to the lack of a reliable biomarker in the clinic, timely detection of DCI is currently highly challenging. In fact, its onset is often missed despite the multimodal monitoring in intensive care, with severe consequences for the patient: Secondary infarctions may lead to severe disability or even death. This project aims at developing a novel bedside measurement system to monitor and predict the risk for DCI in the hospital, filling the current diagnostic gap.
Keywords
Biomedical engineering, clinical data analysis, system modeling, state estimation
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Semester Project , Master Thesis
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Published since: 2024-12-03 , Earliest start: 2025-01-10 , Latest end: 2025-12-19
Organization Research Zeilinger
Hosts Heim Marco
Topics Engineering and Technology
Error bounds for scalable Gaussian process regression
The goal of the project consists in deriving error bounds for the approximate Gaussian process regression method given by the FITC method.
Keywords
Gaussian processes, uncertainty bounds
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Semester Project , Master Thesis
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Published since: 2024-12-02
Organization Research Zeilinger
Hosts Scampicchio Anna
Topics Engineering and Technology
Error bounds for Regularized Trigonometric Regression in the Multi-task setting
Multi-task learning is the problem of jointly learning multiple functions that are “related” to each other. By leveraging this similarity, estimation performance can be improved on each (possibly unseen) task, and one can make an efficient use of the available data. The project aims at deriving uncertainty bounds around the multi-task-system estimates. Specifically, the candidate will work with the regularized trigonometric regression inspired by the so-called sparse-spectrum Gaussian process regression, investigate the issue of bias learning (i.e., finding the features that encode similarity among tasks) and derive error bounds for it, possibly setting the analysis in the statistical learning framework.
Keywords
statistical learning, multi-task learning, uncertainty bounds
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Semester Project , Master Thesis
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Published since: 2024-12-02
Organization Research Zeilinger
Hosts Scampicchio Anna
Topics Engineering and Technology
Direct Projects
The projects from Prof. Melanie Zeilinger's group are hosted on the student projects page.
Custom Projects
From time to time, project supervisors will develop custom student research projects to fit with a student's particular interests or skills.
If you are interested in doing a custom student research project, please email the project supervisor of your choice directly. We recommend that you carefully review their area of research before you contact them.
Please note that the decision of whether to develop a custom student project is at the full discretion of the project supervisor.