Semester and Thesis Projects
The ETH AI Center offers a wide range of semester and thesis projects for students at ETH Zurich, as well as other universities. Please see the list below for projects that are currently available.
How do you publish a thesis or semester project with the ETH AI Center?
- Academia: If you are affiliated with the ETH AI Center as faculty member, post- or doctoral fellow, please add the following affiliation to your Sirop account. If you tag your thesis project with this affiliation, it should appear in the list below.
- 'ETH Competence Center - ETH AI Center (ETHZ)'
- Industry: If you represent a company that has a corporate partnership with the ETH AI Center, please contact .
Need help?
- We provide a external page template for thesis projects accouncements that you can use for your upcoming project & upload to external page SiROP.
- Is your thesis project still missing from the list below? We are constantly adding new thesis projects that are available within the ETH AI Center.
- Are you a student? Check out our Semester and Thesis projects below!
Facial aging simulation
Facial aging simulation is an important problem in biometrics, healthcare, digital human modeling, and computer graphics. Accurately modeling how a human face changes over time is crucial for applications such as age-invariant face recognition, forensic analysis, and realistic digital avatars. Traditional approaches mainly rely on 2D image-based transformations, which can produce visually convincing results but fail to capture underlying 3D geometric changes and often lack consistency across pose and viewpoint. Recent advances in deep generative models and 3D face representations have enabled more realistic and controllable aging simulation. Cycle-consistent GAN-based methods allow unpaired age translation in 2D images [1–3], while datasets such as AgeSynth provide benchmarks for biometric aging evaluation [4]. In parallel, 3D facial modeling techniques enable explicit manipulation of geometry and fine-scale surface details [5,6]. However, most existing methods treat 2D and 3D aging separately and lack a unified framework that jointly models texture, geometry, and identity across time.
Keywords
deep generative models. 3D face representations.
Labels
Semester Project , Collaboration , Internship , Master Thesis
Description
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Published since: 2026-05-21 , Earliest start: 2026-05-01
Organization ETH Competence Center - ETH AI Center
Hosts Davoudi Neda
Topics Information, Computing and Communication Sciences
Facial Aging Simulation
This project proposes a unified 3D-aware facial aging simulation framework for realistic age progression and regression from both 2D and 3D data. Unlike traditional 2D-only methods, the approach jointly models texture, geometry, and identity over time using generative models and 3D representations. It emphasizes identity preservation, interpretable age–identity disentanglement, and cross-view consistency through hybrid 2D–3D pipelines. The framework will be evaluated on age-invariant face recognition and biometric robustness.
Keywords
computer vision, 3D, generative AI, image processing, machine learning, deep learning
Labels
Internship , Master Thesis
Description
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Published since: 2026-05-21 , Earliest start: 2026-05-21 , Latest end: 2027-05-31
Organization ETH Competence Center - ETH AI Center
Hosts Davoudi Neda
Topics Engineering and Technology
Fine-Tuning Multimodal Reasoning Models for Affordance and Manipulativity Prediction in Robotic Manipulation
This project investigates whether reasoning-oriented multimodal models such as Gemma 4 can be fine-tuned to predict task-relevant affordances and manipulability for robotic manipulation. Given visual observations and high-level instructions, the model will identify actionable object parts, infer their functional suitability, and estimate how effectively a robot can interact with them using its own embodiment. Predictions may include affordance classes, contact regions, or manipulability scores learned from demonstrations, simulation, or robot execution data. These outputs will support interaction selection directly or guide downstream planners and control policies. The approach will be evaluated in simulation and on real robotic platforms to improve task-aware manipulation success in unstructured environments.
Keywords
affordance prediction; robotic manipulation; manipulability; multimodal reasoning; vision-language models; task-aware interaction; object part affordances; embodied AI; contact region prediction; motion planning; robot learning; high-level instruction understanding
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Master Thesis
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Published since: 2026-05-10 , Earliest start: 2026-05-06 , Latest end: 2027-04-08
Applications limited to ETH Zurich , University of Zurich
Organization Robotic Systems Lab
Hosts Zurbrügg René , Werner Lennart
Topics Engineering and Technology
Constrained Reinforcement Learning for Robot Navigation
This project proposes a Constrained Reinforcement Learning (CRL) framework for social robot navigation that explicitly enforces safety, smoothness, and social-distance constraints. Unlike traditional reward-based RL, the approach integrates multiple constraints and a safety filter to ensure robust and human-compliant navigation across varying crowd conditions.
Keywords
Constrained Reinforcement Learning (CRL) Social Navigation Robot Navigation Safety Constraints Human-Aware Navigation
Labels
Master Thesis
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Published since: 2026-05-05 , Earliest start: 2026-09-01 , Latest end: 2027-04-30
Organization Spinal Cord Injury & Artificial Intelligence Lab
Hosts Alyassi Rashid , Alyassi Rashid , Alyassi Rashid
Topics Engineering and Technology
Learning-based Mapping for Robot crowd-aware Navigation
Learning-based crowd mapping predicts global crowd density and flow from sparse robot observations, enabling crowd-aware global planning beyond local perception. The approach integrates multi-modal priors (e.g., calendars via LLMs) to capture temporal patterns and is validated in simulation and real-world navigation tasks.
Keywords
SLAM Crowd mapping Robot navigation Global planning LLMs Spatio-temporal modeling
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Master Thesis
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Published since: 2026-05-05 , Earliest start: 2026-09-01 , Latest end: 2027-03-31
Organization Spinal Cord Injury & Artificial Intelligence Lab
Hosts Alyassi Rashid , Alyassi Rashid , Alyassi Rashid
Topics Engineering and Technology
Reinforcement Learning for Crowd-Aware Robot Navigation
This project focuses on improving RL-based social navigation by creating a simulation framework with diverse and realistic human behaviors. Current RL methods often train on simplified crowds where all pedestrians behave similarly, which limits generalization in real-world environments.
Keywords
RL, Robot Navigation
Labels
Master Thesis
Description
Goal
Contact Details
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Published since: 2026-05-05 , Earliest start: 2026-09-01 , Latest end: 2027-03-31
Applications limited to ETH Zurich
Organization Spinal Cord Injury & Artificial Intelligence Lab
Hosts Alyassi Rashid , Alyassi Rashid , Alyassi Rashid
Topics Engineering and Technology
Learning-based Control and Motion Analysis of Biomimetic Tendon-driven Fish Robot
The student will use a provided simulation and reinforcement learning pipeline to identify and model a real robotic fish, train a control policy, deploy it on hardware, and compare its motion to biological swimming under real-world constraints.
Keywords
robotics, simulation, sim-to-real, underwater
Labels
Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2026-05-01 , Earliest start: 2026-02-16 , Latest end: 2027-03-31
Organization ETH Competence Center - ETH AI Center
Hosts Michelis Mike
Topics Information, Computing and Communication Sciences
Brain Machine Interface - Neuroprosthetics
Join the Sensors Group at the Institute of Neuroinformatics (INI) to develop next-generation visual neuroprosthetics and advance the future of brain-machine interfaces! Topics Include: - implementing real-time computation on embedded platforms (FPGA, uC, jetson) - Virtual Reality for Neuroprosthetic Vision - Fusion of Event Cameras (DVS) and the Meta Aria Glasses - Audio Prosthesis Find the latest projects on our website: https://sensors.ini.ch/student-projects/projects-brain-machine-interfacing/ Application process: Write us about your interests, include CV and transcript, and we can arrange a meeting. We can supervise students from UZH and ETH. We offer semester projects as well as bachelor's and master's theses projects.
Keywords
brain machine interface, visual neuroprosthetics, bmi, neural networks, Real-time computation, Embedded platforms, FPGA, Closed-loop control, neural recording analysis, Control systems, Deep learning, Verilog, Vivado, hls4ml, Hardware acceleration, Jetson, VR, Android, Unity/Blender
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2026-04-24 , Earliest start: 2026-01-01 , Latest end: 2027-12-31
Applications limited to ETH Zurich , University of Zurich
Organization ETH Competence Center - ETH AI Center
Hosts Moure Pehuen , Liu Shih-Chii , Hahn Niklas
Topics Information, Computing and Communication Sciences , Engineering and Technology
Benchmarking Neural Surrogate Models for Computational Fluid Dynamics
Comparing various neural network surrogate models on computational fluid dynamics problems.
Keywords
surrogate modeling, deep learning, fluid simulation
Labels
Semester Project , Internship , Bachelor Thesis
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Published since: 2026-04-03 , Earliest start: 2026-01-01 , Latest end: 2026-12-31
Organization ETH Competence Center - ETH AI Center
Hosts Michelis Mike
Topics Information, Computing and Communication Sciences , Engineering and Technology , Physics
Iterative Optimization for 3D Computational Soft Swimmer Design
Extending an iterative surrogate model optimization framework to include soft bodies with fluid-structure interaction. Design optimization will then be shown in 2D and 3D on passive soft swimmers.
Keywords
surrogate modeling, deep learning, fluid simulation, optimization
Labels
Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2026-04-03 , Earliest start: 2026-01-01 , Latest end: 2026-12-31
Organization ETH Competence Center - ETH AI Center
Hosts Katzschmann Robert, Prof. Dr. , Michelis Mike
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Towards Adaptive Auditory Neural-Network Based Prosthesis
This project focuses on developing targeted sound extraction algorithms for audio prosthesis using audio or audio and vision input.. You will design and implement signal processing techniques and machine learning models tailored for hearing aids or embedded audio devices. The work involves optimizing neural architectures, exploring trade-offs between computation cost and accuracy, and validating the system using real-world audio and visual data or data collected from augmented reality glasses.. Qualifications: Experience with Python, signal processing, and training neural networks, preferably also experience with embedded audio algorithms, VR/AR Application process: Write to us about your interests, CV and transcript, and we can arrange a meeting. We can supervise students from UZH and ETH. We offer semester projects as well as bachelor's and master's thesis projects.
Keywords
audio signal processing, deep neural networks, efficient networks, audio prosthesis, VR/AR, hearing aids
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Semester Project , Bachelor Thesis , Master Thesis , Other specific labels , ETH Zurich (ETHZ)
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Published since: 2026-02-03 , Earliest start: 2025-11-17
Applications limited to ETH Zurich , University of Zurich
Organization ETH Competence Center - ETH AI Center
Hosts Liu Shih-Chii
Topics Information, Computing and Communication Sciences , Engineering and Technology