GPT-Lab is a generative AI research group at Tampere University in Finland, founded in June 2023 by Professor Pekka Abrahamsson. It researches generative AI and software engineering across eight pillars, from the technical core of AI to its societal impact.

GPT-Lab was founded by Prof. Pekka Abrahamsson and is headed by Dr. Kai-Kristian Kemell, with campus leads Dr. Mika Saari in Pori, Dr. Muhammad Waseem in Tampere, and Dr. Jussi Rasku in Seinäjoki.

Where is GPT-Lab located?

GPT-Lab operates across three campuses in Finland: the University Consortium of Pori, Tampere University's Hervanta campus, and the University Consortium of Seinäjoki, with international operations extending to GPT-Lab Nordics and GPT-Lab Africa.

How can a company work with GPT-Lab?

Companies can start with a free discovery meeting with a GPT-Lab researcher, then progress through a 90-minute consultation, a half-day workshop, a 4-week pilot solution, or the 6-week Adopt an AI Researcher programme.

What is GPT-Lab's Demo Showroom?

The Demo Showroom, hosted at demo.gpt-lab.eu, is GPT-Lab's public gallery of generative AI prototypes and demos built by its researchers and students.

Master Thesis Topic Bank

GPT-Lab · Tampere University

Master Thesis Topic Bank

Welcome to the Master Thesis Topic Bank at GPT-Lab! This resource provides a curated list of thesis topics for master's students at Tampere University who wish to conduct their thesis in the fields of artificial intelligence and software engineering. Here, you’ll find a variety of predefined topics that reflect the cutting-edge research happening at GPT-Lab. Each topic is designed to align with our core focus areas, providing you with opportunities to contribute to innovative projects.

You are encouraged to select a topic from the list or propose your own in the registration form, provided it falls within the scope of AI and software engineering. Whether you’re passionate about natural language processing, machine learning, or software development, you’ll find exciting opportunities that match your academic and research interests.

For those proposing their own topics, please ensure they meet the criteria and are relevant to our ongoing research themes.

How it works

Browse Topics

Review the list of available thesis topics, each with a brief description.

Select or Propose

Choose a topic or propose your own idea during the application process.

Get Started

Once your application is accepted, you will be paired with an advisor to begin your research journey.

Open the registration form Scroll down to browse the available topics.

Disclaimer: For the best viewing experience, please access this table on a desktop device.

Last updated: 07.10.2026

Status	Thesis topic	Description	Supervisor/Thesis advisor
Available	Ethical issues in AI agents and multi-agent collaboration: a systematic literature review	As AI continues to progress, hypothetical future risks become the reality of today. AI agents, both lone agents and AI agents working collaboratively, present various promises across a wide variety of industries, but also various risks. Discussion on these systems has accelerated with recent advances in Generative AI (GenAI) and Large Language Models (LLMs).	Kai-Kristian Kemell
Available	From RPA Code to BPMN Process Diagrams	This thesis investigates methods for automatically transforming robotic process automation (RPA) code into BPMN process diagrams to improve process transparency, maintainability, and integration with business process management tools. The work involves analysing RPA scripts, defining mappings to BPMN constructs, and prototyping a converter. The topic comes from Seinäjoki-based IT-consultation company River IT and details of collaboration can be agreed upon. Prerequisites include solid programming skills, understanding of RPA platforms and BPMN modelling, and ability to read and formalise code-to-model transformations.	Jussi Rasku
Available	Gameful LLM-Based Multi-Agent Systems	This thesis aims to assess what gameful elements can effectivelly influence a Multi-Agent system's performance in coding tasks. By introducing gameful elements in a Multi-Agent system, we hope to encourage collaboration (or competittion), leading to more refined output. Prerequisites: Familiarity with how ML/LLM models work (training, evaluation, datasets, etc.) Willingness to learn or experience with interviews, thematic analysis, or survey design	José Siqueira de Cerqueira
Available	Impact of generated PlantUML diagrams to large language model generated code accuracy	The performance of a LLM generating or fixing code is dependent on the correct context in which the edits are made. Hence, the research question is: Can the performance of the coder AI be improved by enriching the prompt with generated UML diagrams? The diagrams are to be generated from relevant project source files and given to the LLM using a suitable DSL such as PlantUML. The feasibility of the approach is tested on SWE- bench, some subset of that, or some other coding benchmark. Prerequisites: The student has experience in using coding LLMs such as Github Copilot, Qwen 2.5, Mistral or DeepSeek Coder. Also, one should be fluent in creating and reading UML, know how to write PlantUML, and be interested in empirical testing of software tools.	Jussi Rasku
Available	Smart and Sustainable Energy Consumption Optimization with IoT and LLMs	Are you interested in developing AI-powered solutions for energy efficiency? This Master's thesis project focuses on creating an IoT-based energy management system where Large Language Models (LLMs) analyze and optimize energy consumption. The project could involve integrating energy meters and IoT sensors, such as temperature, humidity, and electricity usage monitors. It could also include developing AI-driven analytics to provide smart recommendations for optimizing energy consumption. Additionally, a user-friendly interface could be created for energy management and forecasting. By reducing energy consumption and improving decision-making, this project contributes to sustainability and the circular economy. If you are passionate about AI, IoT, and green technology, this is your chance to make an impact. Prerequisites: Python, LLM. IoT -devices Possibility to use/implement APIs: https://github.com/Green-Software-Foundation	Mika Saari
Available	Sustainable Software Engineering with AI	Examples of possible topics: "Reducing the Carbon Footprint of AI Model Training: A Study on Pruning, Quantization, and Transfer Learning", "Life Cycle Assessment of AI Models: From Training to Deployment", "AI-Specific Hardware for Green Computing: A Comparative Study of GPUs, TPUs, and AI Chips" Prerequisites: https://github.com/Green-Software-Foundation	Mika Saari
Available	From Retrieval to Context Engineering: Task-Aware Context Construction for Agentic RAG	This thesis studies how Agentic RAG systems can go beyond simple top-k document retrieval. Instead of only selecting the most similar chunks, the system builds context based on the user’s task, intent, retrieval needs, and expected answer. The study focuses on task understanding, retrieval planning, context selection, filtering, and answer verification before producing the final response. Prerequisites: Python, basic RAG knowledge, LLM agents, vector databases, prompt engineering, basic evaluation methods	Toufique Hasan
Available	Reverse Engineering Requirements Specifications from Existing Software Products	This thesis investigates how requirements specifications can be reconstructed from an existing software product when the original requirements are missing, incomplete, or outdated. The work will explore what information can be extracted from sources such as the software itself, user interfaces, documentation, source code, tests, and other available project artifacts, and how this information can be used to recover functional and non-functional requirements. The thesis may include the development and evaluation of an AI-assisted approach for generating a structured requirements specification from an existing product. Prerequisites: Basic knowledge of requirements engineering and software engineering. Programming skills and familiarity with LLMs or AI-assisted software engineering are beneficial.	Risha Parveen, Zheying Zhang
Available	Improving Trustworthiness and Traceability in AI-Generated Product Vision Documents	This thesis investigates how AI-assisted generation of software product vision documents can be improved to produce more trustworthy and traceable results. The work will explore approaches for ensuring that generated content is grounded in the available project information, that important statements can be traced back to their supporting sources, and that unsupported or incorrect information is reduced. The thesis will involve improving an existing approach and evaluating the quality, trustworthiness, and traceability of the generated vision documents. Prerequisites: Basic knowledge of software engineering and requirements engineering. Programming skills and familiarity with LLMs, prompt engineering, or retrieval-based AI systems are beneficial.	Risha Parveen, Zheying Zhang
Available	Barriers and enablers of AI governance in organisations	The goal of the thesis is to seek understanding of barriers and enablers that organisations face when trying to govern AI in a meaningful way. Prerequisites: Basic knowledge of responsible AI and AI governance. The most important is having interest towards understanding organisational aspects of AI adoption and how it can be done in an ethically and societally sustainable way.	Salla Westerstrand
Available	LLM-Coordinated Multi-Agent Reinforcement