Teaching & theses

In the spring term 2026, we are teaching:

• Mobile Health and Activity Monitoring 2026 master course
• Adaptive User Interfaces through Machine Learning 2026 bachelor seminar
• Egocentric Computer Vision: Perception and Understanding from the First-Person View 2026 master seminar
• Reinforcement Learning for Understanding and Modeling Human Behavior 2026 master seminar

Available student thesis projects

7 projects are available (via 6 master’s theses, 5 semester theses, and 2 bachelor’s theses). The list below is up-to-date.

Please submit your CV and transcripts through SiROP. In case of questions, please contact us via SiROP.

• Geometry-Aware Surface Routing for 3D Object Meshes

  Building on our SIGGRAPH 2026 paper, this project will develop a new geometry-processing method for routing surface-based sensor layouts directly on 3D object meshes. The project will focus on a constructive routing algorithm that generates two compatible families of surface curves and address the geometric challenge of producing well-distributed, surface-conforming curve networks that satisfy routing, intersection, and topology constraints on arbitrary meshes.

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  • contact: Christian Holz
  • master's thesis

  • Geometry processing
  • surface meshes
  • geodesic curves
  • intrinsic routing
  • curve networks
  • vector fields
  • computational fabrication
  • surface parameterization

• Tactile Representations in Robotics via Self-Supervised and Optimal-Transport-Based Learning

  We will develop and validate a self-supervised learning pipeline for tactile representation learning across different tactile datasets and sensor types. Using existing public tactile datasets, we will train tactile encoders on images and align the learned feature spaces using Optimal Transport. The goal is to evaluate whether optimal transport can improve cross-dataset and cross-sensor transfer without requiring exact paired tactile samples.

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  • contact: Berken Demirel
  • master's thesis

  • self-supervised learning
  • optimal transport
  • representation learning
  • tactile

• Wearable Data Pipeline for Cardiac Health Monitoring

  The goal of this student project is to design and implement a fully automated data ingestion and processing pipeline for health data collected 24/7 via a Polar Watch from patients.
  The study with data collection will last a year to study the cardiac activity of people under different daily life activities.

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  • contact: Elsie Nix, Berken Demirel
  • semester thesis
  • bachelor's thesis

  • cardiac disease
  • digital health
  • wearables

• Reasoning for Implicit Hand-Object Contact Estimation from Monocular RGB

  This project explores a new approach to hand-object interaction by predicting dense physical contact directly on the surfaces of the hand and object. Given only a monocular RGB image and a canonical 3D object template, we will develop a model for interaction-aware reasoning that infers object-space contact without relying on explicit poses. The project draws on current directions in canonical-space prediction, physically grounded scene understanding, and 3D correspondence learning to reason about visual evidence of contact regions on the object surface.

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  • contact: Andela Ilic
  • semester thesis
  • master's thesis

  • Computer Vision
  • Hand-Object Interaction
  • 3D Vision
  • Contact Estimation
  • Monocular Reconstruction
  • Geometric Deep Learning
  • Interaction-Aware Learning

• Making AI agents robust for using imperfect tools

  Tool-augmented LLM agents often rely on tools that are usually correct but can occasionally return plausible, incorrect outputs. In this project, we will mitigate these silent errors through a cost-aware strategy that combines cross-tool consistency checks with targeted verification at high-risk steps.

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  • contact: Tommaso Bendinelli
  • semester thesis
  • master's thesis

  • Agent reliability
  • Tool-augmented LLM Agents
  • Robust reasoning

• Benchmarking agentic reasoning robustness on time series

  We will create a research benchmark for evaluating AI agents on decision making from time series. Our benchmark will integrate simulations that expose realistic reasoning failures and edge cases. We will evaluate open-source agentic systems using this benchmark on robustness, reliability, and cost-aware performance.
  The project combines benchmark engineering, controlled experimentation, and empirical analysis to identify which agentic strategies are reliable in realistic time-series decision settings.

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  • contact: Tommaso Bendinelli
  • semester thesis
  • master's thesis

  • ⁠Time-series reasoning
  • Agent reliability
  • Benchmark design
  • AI

• + 1 internal project (must be inside ETHZ network)

  

Current thesis students

• Tim Goppelsroeder master's ETH Data Science, D-INFK
• Nicolas Baeriswyl master's ETH Computer Science, D-INFK
• Qi Ma master's ETH Computer Science, D-INFK
• William Jabbour master's ETH Data Science, D-INFK
• Rafael del Rio Alfonso master's TU/e Electrical Engineering
• Yannic Hostettler semester ETH Robotics, D-MAVT, RSC
• Fei Gao semester UZH Computer Science

Past Courses and Seminars

• Human-Computer Interaction bachelor course
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
• Mixed Reality master course
  • 2025
  • 2024
  • 2023
• Mobile Health and Activity Monitoring master course
  • 2025
  • 2024
  • 2023
  • 2022
• Ubiquitous Computing master course
  • 2021
  • 2020
• Adaptive User Interfaces through Machine Learning bachelor seminar
  • 2025
• Egocentric Perception for Human-World Understanding master seminar
  • 2025
• Reinforcement Learning for Understanding and Modeling Human Behavior master seminar
  • 2025
• Advanced Topics in Mixed Reality bachelor seminar
  • 2024
  • 2023
  • 2022
• Advanced Topics in Technical Human-Computer Interaction bachelor seminar
  • 2021
  • 2020