Open Positions/ Theses

Open Positions

BSc-MSc Thesis Topics – Open Continuously

 The Interactive Technologies group has openings for the following BSc-MSc thesis topics. Our group is widely interested in projects that will assist surgeons in general and neurosurgeons in particular with improved performance and training skills. To this end, our researchers and students actively collaborate with NeuroCenter Neurosurgery and Microsurgery Center (Itä-Suomen Mikrokirurgiakeskus) at Kuopio University Hospital and other prestigious departments of neurosurgery in Finland and Canada. Joining this group will allow you to explore various multi- and interdisciplinary projects related to the following topics and skills: 

  • Intelligent user interfaces, human-computer interaction, brain-computer interfaces, computer-supported cooperative work, educational technology, and computing education,
  • Multisensory perception, motor skill training/learning, cognitive neuroscience, and affective computing, 
  • Eye tracking, computational evaluation of microsurgical skills, automatic video content analysis, real-time object-tracking, robotics, and dementia diagnosis,  
  • Signal processing, deep learning, computer vision, medical computing, and health Informatics. 

Please note that the listed BSc thesis projects will include a literature review, final report, and a short practical demo or project. MSc versions will include extended practical work and ideally lead to a thesis and a conference/journal paper. For master’s students, joint project and supervision with the department of Applied Physics is possible.

Topic 1: Using Brain-Computer Interfaces in Surgical Skill Training: A Literature Review and Interface Design  

Brain-Computer Interfaces (BCIs) are systems that enable direct communication between the brain and external devices by recording and interpreting simple features from brain electromagnetic activity. Historically, BCIs have been used to help patients with limited or no muscular control, such as amyotrophic lateral sclerosis (ALS) and stroke patients, to gain relative independence in their daily lives. Driving wheelchairs or controlling robotic arms or legs are famous examples of such applications. However, in this project, we would like to explore the use of BCIs in teaching surgical skills to healthy individuals. The student should conduct a literature review on the use of different BCI paradigms, such as motor imagery and P300 spellers, in training surgical students, and find examples of BCIs being used in real operating rooms. The student can complete the work by working with our own g.tec EEG headsets and software to design a simple paradigm and record data from volunteers in the lab under direct supervision. English-language progress report, final report, and final presentation are required. This project can be extended into a master’s project upon the agreement of the student and supervisors.

Topic 2: Using Augmented and Extended Reality (AR/XR) in Surgery: A Literature Review and Interface Design  

Augmented reality (AR) and extended reality (XR) are simulated experiments that combine and extend digital world environments with perceptions of real world and allow the users to interact with that world in real time. Recently, several companies have designed these applications for surgical training and planning and even used them in real surgeries. In this project, the student should first conduct a literature review on state-of-the-art VR/AR/XR systems used in surgery and identify key aspects of their paradigms. Next, they can use the HTC Vive headsets in our laboratory to design a simple XR environment to interact with surgical tools. English-language progress report, final report, and final presentation are required. This project can be extended into a master’s project to combine XR with eye-tracking and EEG headsets upon the agreement of the student and supervisors.

Topic 3: Will you perform better if you watch others do it first? A Review of Action Observation in Skilled Performance for Athletes and Other Operators  

In neuroscience studies, it is known that when people imagine doing a task such as moving their arms, or when they watch others do the task, their brains react almost the same as if they were doing that activity themselves. This concept has been used for rehabilitation in stroke patients and skill training in surgeons and athletes. In this project, the student is asked to perform a literature review of experiments using “action observation, motor imagery, and action execution” in athletes and other operators of fine, skilled tasks. They will then help with designing an experiment to record eye movements and brain activities of participants in the lab during these three phases. English-language progress report, final report, and final presentation are required. This project can be extended into a master’s project to upon the agreement of the student and their supervisors.

Topic 4: Repeat after Me: A Real-time Microtool Movement Detection and Cue 

Using a mobile phone and/or web-cam and a display in this topic we will develop an application that will first play a short clip consisting of tool movement and operation and then record how a user performs the same. It will then compute a similarity of the two performances and provide feedback to the user. Computer vision (OpenCV) skills and programming skills are required.

Topic 5: Deep Learning, Graph Signal Processing, and Connectivity Models for Emotion Classification and Attention Prediction using EEG Signals (Up to 4 students) 

Although brain is composed of several highly developed and specialized cortices, these physical tissues are actively engaged in short- and long-range communication to satisfy all the sensorimotor and cognitive needs of their humans. Brain imaging, cognitive neuroscience, and affective computing are highly dependent on advanced signal and image processing tools to model structural, functional, and causal dynamics among these networks. Furthermore, emotion and attention classification using scalp EEG and without explicit communication enables automated recognition for people suffering from developmental disorders, stroke, and the like. We will use public and private EEG datasets and develop new pipelines to study attention skills and emotion classification. These projects require basic signal processing knowledge, programming skills in Matlab or Python, and strong ability and interest in independent and multidisciplinary studies. 

To learn more about the listed topics or schedule a meeting with a group member from the Interactive Technologies research group,  or Prof. Roman Bednarik (

In your emails, please attach transcripts and academic CV, and include one paragraph to explain why you are interested in these topics. Your CV should include the following key pieces of information: Education History, Independent Studies, Academic Projects, Internship/Work History – all followed by a list of accomplished tasks and results, Programming Languages, Software Tools, and Data Science or Engineering Skills. We look forward to working and learning with you.