We welcome new thesis students twice a year, at the beginning of each semester — in April and October.
We only accept applications during the designated periods (please check back ahead of the semester start for exact aplication dates).
To ensure a good fit between students and supervisors, topics are limited and may be tailored to ongoing research projects within the group.
Expression of Interest
Students can write to hci-thesis.informatik@lists.hu-berlin.de to ask for topics or apply with their own one.
Application Process Overview
- There are two main time windows for application, normally in September and March. We are starting with the process in the winter semester 2025/2026 later as we are introducing a new process (October 2025).
- Within these windows students can apply for an open topic.
- Students can apply for a topic by sending us a proposal. A proposal must be submitted until the deadline for this cycle (November 10th 2025) and must contain the following headlines:
- Motivation
- Related Work
- Research Questions and/or Hypotheses
- Methodology with how you envision to execute your study for answering the research questions/hypotheses, including your measures.
- We collect your applications and suitable proposals will make a topic-student assignment.
- Once a student has been matched to a supervisor, a kick-off meeting is scheduled to scope the topic.
- The thesis will be registered immediately after the proposal and the goals in the kick-off meeting were approved.
- Once the thesis work is concluded, the thesis defense is scheduled within a dedicated defense slot.
Important Dates
- Submission deadline for the winter semester 2025/2026: November 10th 2025.
- Submission deadline for the summer semester 2026: March 31st 2026.
Please consider the following hints and guidelines for working on your thesis:
- Templates for thesis and proposal: https://www.informatik.hu-berlin.de/de/studium/formulare/vorlagen.
- In addition a list of aids used (more details below) must be included after the declaration of authorship.
- Page limits are as follows:
- page limit is for Bachelor Informatik 40 pages and for Kombibachelor Lehramt Informatik 30 pages.
- page limit is for Master Informatik 80 pages and for Master Information Systems 60 pages.
- The limits do not include cover, table of content, references, and appendices.
List of Aids Used
As generative AI tools evolve, it is important to clearly declare all the tools and aids used in your thesis work to ensure transparency in presenting your personal performance. Such transparency also acts as an important safeguards against accusations of academic fraud.
All aids must therefore be reported in the form of a table, accompanied by a signed declaration of “list of aids used”. Such table is required even in cases where no aids were used.
This table must be placed behind the authorship declaration in a separate page in the thesis and must include at least the following columns:
- aids/tools used – which tools was a used (e.g., ChatGPT, Deepl, Gemini, etc.).
- type(s) of use – explaining what was its use (e.g., ChatGPT was used to improve the writing style, limited to editing).
- affected areas/chapters – where are the results of tools affecting the thesis (e.g., chapter “Research methodology” p. 15 – 18).
- documentation of the tool – a link to the documentation of the tool (e.g., link to ChatGPT’s help page).
Finally, below is an example of a signed declaration that must follow the list of aids table:
- “I hereby declare that I have listed all the aids I have used in the list above.”
- If no aids have been used, it is also indicated in the list (to be listed under “Aids/tools used: none”)
- Signature
We hope that this will help increasing transparency and protect you against academic fraud.
*Credits to WU Vienna
Topics for the Winter Semester 2025/2026
Evaluating and Classifying Travel Experiences of Cyclists
This topic investigates how well contextual smartphone data can serve as predictor of cyclist satisfaction. The goal is to identify patterns that characterize different types of cycling experiences such as comfort, stress, or enjoyment. Using machine learning and data-driven modeling, the goal of this thesis is to develop classification approaches that can automatically infer cyclists’ experiential states from multimodal input. The thesis includes the development of an interactive application that routes after regular cycling experiences.
- Sönmez, S. F., & Graefe, A. R. (1998). Determining future travel behavior from past travel experience and perceptions of risk and safety. Journal of travel research, 37(2), 171-177.
- Kim, J. H. (2010). Determining the factors affecting the memorable nature of travel experiences. Journal of Travel & Tourism Marketing, 27(8), 780-796.
- Bethge, D., Kosch, T., Grosse-Puppendahl, T., Chuang, L. L., Kari, M., Jagaciak, A., & Schmidt, A. (2021, October). Vemotion: Using driving context for indirect emotion prediction in real-time. In The 34th annual ACM symposium on user interface software and technology (pp. 638-651).
Evaluating an IDE for Designing Data Analysis Workflows
This thesis focuses on n-wave, an early prototype of an integrated development environment for data analysis workflows. The project aims to conduct a formative, user-centered evaluation of n-wave, testing its functionality, usability, and overall workflow design. The student will work with DAW users to identify strengths, limitations, and opportunities for improvement, providing concrete design insights that guide the next development phase of the system.
- Stoudt, S., Vásquez, V. N., & Martinez, C. C. (2021). Principles for data analysis workflows. PLOS Computational Biology, 17(3), e1008770.
- Costa, L., Barbosa, S., & Cunha, J. (2023, October). Towards an IDE for Scientific Computational Experiments. In 2023 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) (pp. 290-292). IEEE.
Implementation of Pocket Interaction
This thesis topic explores how smartphone orientation inside the pocket can be used as an input modality for subtle, on-body interaction. Building on prior work that classified pocket orientations using machine learning, this project focuses on designing and implementing an interactive application that leverages this capability for real-time interaction. The goal is to prototype and evaluate use cases, such as context-aware notifications, gesture-based controls, or implicit status detection—and assess their usability and technical feasibility. The work bridges sensing and interaction design, advancing the concept of seamless, unobtrusive interfaces integrated into everyday behavior.
- Miao, F., He, Y., Liu, J., Li, Y., & Ayoola, I. (2015). Identifying typical physical activity on smartphone with varying positions and orientations. Biomedical engineering online, 14(1), 32.
- Kusber, R., Memon, A. Q., Kroll, D., & David, K. (2015, September). Direction detection of users independent of smartphone orientations. In 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall) (pp. 1-6). IEEE.
Deepfake Detection using Eye Tracking and Electroencephalography
This thesis investigates how physiological and behavioral signals can reveal cognitive and perceptual differences when humans view authentic versus AI-generated (deepfake) videos. Building on recent advances in multimodal deception detection, the project combines eye tracking and electroencephalography to explore how gaze patterns and neural responses reflect user confidence, attention, and engagement with deep fakes. The goal is to identify reliable indicators that distinguish between real and synthetic content and to model how humans process visual authenticity.
- Tauscher, J. P., Castillo, S., Bosse, S., & Magnor, M. (2021, September). EEG-based Analysis of the Impact of Familiarity in the Perception of Deepfake Videos. In 2021 ieee international conference on image processing (icip) (pp. 160-164). IEEE.
- Khan, M. R., Mir, H., Al Shargie, F., Tariq, U., Dhall, A., Naeem, S., … & Al Nashash, H. (2024, July). Discrimination of Real and Deep Fake Videos using EEG Signals. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1-4). IEEE.
Evaluating Electroencephalography as Measure for the Sense of Agency
This thesis investigates how electroencephalography can be used to quantify the sense of agency—the feeling of control over one’s own actions and their outcomes. The project involves designing and conducting an experimental study in which participants perform tasks that manipulate agency while EEG data is recorded. The goal is to identify neural markers associated with varying levels of perceived control and evaluate EEG’s suitability as an objective measure of agency. The findings will inform future work on implicit measures of agency in human–computer interaction and adaptive interfaces that respond to users’ cognitive states.
- Kang, S. Y., Im, C. H., Shim, M., Nahab, F. B., Park, J., Kim, D. W., … & Hallett, M. (2015). Brain networks responsible for sense of agency: an EEG study. PloS one, 10(8), e0135261.
- Jeunet, C., Albert, L., Argelaguet, F., & Lécuyer, A. (2018). “Do you feel in control?”: towards novel approaches to characterise, manipulate and measure the sense of agency in virtual environments. IEEE transactions on visualization and computer graphics, 24(4), 1486-1495.