Teaching & theses

In the spring term 2025, we are teaching the following courses:

• Mobile Health and Activity Monitoring 2025 master's course
• Adaptive User Interfaces through Machine Learning 2025 bachelor's seminar
• Egocentric Perception for Human-World Understanding 2025 master's seminar
• Reinforcement Learning for Understanding and Modeling Human Behavior 2025 master's seminar

Available student thesis projects

Please directly apply through SiROP with your CV and transcripts. Contact the listed team member(s) in case of questions or email Max Moebus for all general inquiries about bachelor's and master's theses. Email addresses are firstname.lastname@inf.ethz.ch.

• Virtual Reality Avatars to support Learning and Education

  We will explore the design space of avatars in Virtual Reality to support learning and creativity. The project will leverage the concept of "embodied cognition", a set of theories that imply that our bodies and their interaction with the environment can impact how we learn. We will develop a Unity3D-based VR environment for embodied learning that can be deployed on everyday VR headsets.
  
  • contact: Dr. Julia, Chatain, Yi-Chi Liao
  • Semester Project
  • Master Thesis

  • Computer Graphics
  • Computer Vision
  • Visualization
  • Rendering
  • Interaction
  • Human Motion
  • Embodiment
  • Embodied Interaction
  • Embodied Learning

• Benchmarking Deep Learning-Based Pose Estimation from Sparse IMUs

  Human pose estimation from a small number of body-worn inertial measurement units (IMUs), such as accelerometers and gyroscopes, holds great potential for practical applications in areas like augmented and virtual reality (AR/VR) and healthcare. While recent advances in deep learning have significantly improved the accuracy of such methods, the lack of standardization in training protocols, evaluation metrics, and datasets makes consistent benchmarking and comparison difficult. This project aims to address this gap by developing a standardized benchmark and evaluation platform for sparse IMU-based pose estimation methods. The platform will include automated evaluation tools and a simple web interface. Ideally, it will be accompanied by a newly recorded motion benchmark dataset. In the case of exceptional progress, the project may lead to a publication.
  
  • contact: Dominik Hollidt, Jiaxi Jiang
  • Semester Project
  • Bachelor Thesis

  • pose estimation
  • deep learning
  • machine learning
  • computer vision
  • benchmark
  • dataset

• Eye Landmark Detection from Head-worn Cameras

  Egocentric vision systems, such as AR/VR headsets and smart glasses, are equipped with eye-tracking cameras that provide a unique perspective for understanding user interactions and physiological states. However, accurately detecting eye landmarks (e.g., eyelid contours, pupil position) from these cameras remains a challenge due to extreme close-up views and motion. In this project, we aim to develop a robust eye landmark detection model tailored for egocentric perspectives, improving downstream applications.
  
  • contact: Björn Braun
  • Semester Project
  • Master Thesis

  • computer vision
  • deep learning
  • machine learning
  • eye landmarks
  • AR
  • VR

• Machine Learning-based Non-Stationary Time-Series Forecasting

  Time series forecasting plays a critical role in understanding and predicting dynamic systems across various domains, including healthcare, and environmental monitoring. However, accurately forecasting non-stationary signals—data characterized by changing statistical properties over time—remains a significant challenge. This project aims to investigate the effectiveness of current machine learning-based forecasting models in predicting non-stationary events. By evaluating the performance of established methods such as GPT-based approaches on real-world non-stationary datasets, this study seeks to identify their strengths, limitations, and applicability.
  
  • contact: Berken Demirel
  • Semester Project
  • Master Thesis

  • forecasting
  • non-stationary process analysis

Current thesis students

• Boris Bernegger master's ETH Computer Science, D-INFK
• Philipp Braune master's ETH Computer Science, D-INFK
• Clemens Keusch master's ETH Computer Science, D-INFK
• Philipp Trachsel master's ETH Computer Science, D-INFK
• Jan-Oliver Seidenfuss master's ETH Electrical Engineering, D-ITET
• Shivangi Tanwar master's UZH Computer Science

• Jingjing Qiu semester ETH Electrical Engineering, D-ITET

• Nicola Witzig bachelor's ETH Computer Science, D-INFK

Past master's thesis students

• Spyridon Garyfallidis (ETH Robotics, D-MAVT)
• Rachel Schuchert (ETH Computer Science, D-INFK)
• Shuyue Wang (ETH Computer Science, D-INFK)
• Andela Ilic (ETH Electrical Engineering, D-ITET) ➤ led to IJCAI 2025 publication Full-Body Pose from Loose IMUs.
• Ying Xue (ETH Computer Science, D-INFK). next: PhD student with us.
• Yao Song (UZH Computer Science)
• Lars Hauptmann (ETH Electrical Engineering, D-ITET) ➤ led to IEEE JBHI 2025 publication Nightbeat.
• Xuejing Luo (ETH Robotics, D-MAVT, RSC) ➤ led to ECCV 2024 publication MANIKIN. next: PhD student at Aalto University.
• He Liu (UZH Data Science, UZH OEC). next: Full-stack developer at intonate.
• Xintong Liu (ETH Robotics, D-MAVT, RSC) ➤ led to IJCAI 2025 publication Full-Body Pose from Loose IMUs.
• Sebastian Reidy (ETH Electrical Engineering, D-ITET). next: Software engineer at Helbling Technik AG, Lenzburg.
• Ailin Liu (RWTH, Data Science). next: PhD student at LMU Munich.
• Adriana Mohap (UZH Data Science). next: Scientific assistant at ETH Zürich.
• Andreas Brombach (ETH Computer Science, D-INFK) ➤ led to ACM IMWUT 2024 publication Detecting Users' Emotional States.
• Rayan Armani (ETH Robotics, D-MAVT, RSC) ➤ led to ACM SIGGRAPH 2024 publication Ultra Inertial Poser. next: Research assistant with us.
• Thomas Roberts (ETH Computer Science / Imperial College London) ➤ led to ACM CHI 2023 publication InfinitePaint. next: PhD student at University of Zürich.
• Guy Luethi (ETH Computer Science, D-INFK) ➤ led to ACM UIST 2022 publication DeltaPen. next: Embedded software engineer at CyOne Security AG.
• Huajian Qiu (EPFL Computational Science) ➤ led to ECCV 2022 publication AvatarPoser. next: Software engineer at Huawei.
• Stephanie Vogt (ETH Robotics, D-MAVT, RSC) ➤ led to IEEE ICRA 2024 publication MiBOT. next: Development engineer at Helbling Technik AG, Zürich.
• Daniel Gstoehl (ETH Computer Science, D-INFK). next: Engineer at Passiv Energie Japan.
• Marilou Beyeler (ETH Computer Science, D-INFK). next: Associate consultant at Netlight.
• Philippe Andreu (ETH Computer Science, D-INFK). next: Machine learning software engineer at Meta, Munich.
• Christian Knieling (ETH Computer Science, D-INFK). next: Software Engineer at ESRI R&D Zürich.
• Nikola Kovacevic (ETH Computer Science, D-INFK) ➤ led to IEEE TAffC 2023 publication Personality Trait Recognition in the Wild. next: PhD student at the Computer Graphics Lab, ETH CS.
• Danil Ivanov (ETH Computer Science, D-INFK). next: Full stack developer at Felfel Zürich.
• Alice Mylaeus (ETH Robotics, D-MAVT, RSC) ➤ led to IEEE ICRA 2024 publication MiBOT. next: APM at Google Zürich.
• Manuel Meier (ETH Electrical Engineering, D-ITET) ➤ led to IEEE VR 2021 publication TapID. next: PhD student with us.

Past bachelor's and semester thesis students

• Liuxin Qing
• Samir Sulaimanov
• Junxiao Cao
• Laurenz Zehetner
• Jakob Schneider
• Jan-Oliver Seidenfuss
• Chang-Jin Lee
• Zhengxu Li
• Yifei Han
• Haoyu Cen
• Philipp Braune
• Aaron Zeller
• Florian Portmann
• Sivalingam Tharmeekan
• Emanuel Mairoll
• Filippo Tognina
• Nicolas Steck ➤ led to ACM UIST 2024 publication SituationAdapt.
• Tim Eilers
• Lukas Teufelberger
• Shao Zhou
• Timo Suess
• Minxuan Qin
• Andela Ilic
• Philipp Trachsel
• Armin Berger
• Nicolas Kopp ➤ led to IEEE JBHI 2025 publication Nightbeat.
• Orestis Oikonomou
• Hyeongkyun Kim
• Alexander Zank
• Filip Stanisic
• Yves Inglin ➤ led to ACM UIST 2024 publication SituationAdapt.
• Yiming Zhao
• Oskar Pilkington
• Jaro Meyer
• Siqi Bao
• He Liu
• Shubham Kumar
• Danilo Dordevic
• Vukasin Bozic
• Julien Wolfensberger ➤ led to IEEE EMBC 2024 publication Unsupervised Sleep Quality Estimation.
• Lara Lenz ➤ led to IEEE TVCG 2024 publication Synchronous vs. Asynchronous Reality.
• Derek Witzig ➤ led to ACM UIST 2023 publication PressurePick.
• Samuel Räber
• Marc Zünd
• Janosch Jungo
• Eren Oner
• Robin Hänni ➤ led to ACM VRST 2024 publication HistoLab VR.
• Seraina Saurenmann
• Bowen Wang
• Stefano Kron
• Robin Rudin
• Rachel Schuchert
• Fabio Bazzi
• Jens Brunner
• Alexander Eichhorn
• Valentin Bieri ➤ led to PMLR UAI 2023 publication BeliefPPG.
• Simon Boehi
• Michael Thomas Schlegel
• Catherine Schmit
• Christoph Salzer
• Cyrill Künzi
• Emanuel Pytlik
• Francois Pailleau
• Joshua Steiner
• Rayan Armani ➤ led to ACM CHI 2023 publication HOOV.
• Thomas Fischer
• Christian Rubin
• Jannik Gartmann
• Markus Pobitzer
• Jonathan Lampérth ➤ led to led to open source release SVG2Keynote.
• Boris Bernegger
• Fabian Mächler
• Yves Kempter
• Janik Baumer
• Guillaume Thivolet
• Lukas Walker
• Tom Cinbis
• Nicole Wenzinger
• Chris Buob
• Clemens Bachmann

Past Courses and Seminars

• Mixed Reality 2024 (fall 2024) master's course
• Human-Computer Interaction 2024 (fall 2024) bachelor's course
• Advanced Topics in Mixed Reality 2024 (spring 2024) bachelor's seminar
• Mobile Health and Activity Monitoring 2024 (spring 2024) master's course
• Mixed Reality 2023 (fall 2023) master's course
• Human-Computer Interaction 2023 (fall 2023) bachelor's course
• Advanced Topics in Mixed Reality 2023 (spring 2023) bachelor's seminar
• Mobile Health and Activity Monitoring 2023 (spring 2023) master's course
• Human-Computer Interaction 2022 (fall 2022, co-taught with Otmar Hilliges) bachelor's course
• Mobile Health and Activity Monitoring 2022 (spring 2022) master's course
• Advanced Topics in Mixed Reality 2022 (spring 2022) bachelor's seminar
• Human-Computer Interaction 2021 (fall 2021, co-taught with Otmar Hilliges) bachelor's course
• Ubiquitous Computing 2021 (spring 2021) master's course
• Advanced Topics in Technical Human-Computer Interaction and Computational Interaction 2021 (spring 2021) bachelor's seminar
• Human-Computer Interaction 2020 (fall 2020, co-taught with Otmar Hilliges) bachelor's course
• CAS ETH: Applied Information Technology, Humans & Machines (fall 2020) CAS CAS
• Ubiquitous Computing 2020 (spring 2020) master's course
• Advanced Topics in Technical Human-Computer Interaction 2020 (spring 2020) bachelor's seminar
• Human-Computer Interaction 2019 (fall 2019, co-taught with Otmar Hilliges) bachelor's course
• CAS ETH: Applied Information Technology, Humans & Machines 2019 (fall 2019) CAS CAS