Thesis work 30hp-AI for understanding human actions from video

Background

Scania is currently undergoing an exciting transformation from a traditional truck manufacturer to a provider of complete sustainable transport solutions. The Smart Factory Lab at Scania is an experimental test environment that explores, assesses, and pilots new technologies before they are adopted in Scania’s production processes. We are looking for motivated and creative students to join our Smart Factory Lab for their master thesis. You will have the opportunity to work in a dynamic and collaborative environment, where you can test and validate new technologies, methods, and solutions in close collaboration with our internal and external stakeholders. To know more about Smart Factory Lab - .

Scania balances work across stations using defined takt times. Today, experienced analysts watch production videos, decompose the operator’s work into discrete actions, and assign a time code to each step. This highlights an opportunity for automation. Recent advances in AI-based video understanding—especially temporal action segmentation—make it feasible to automatically detect fine-grained human actions in videos. Leveraging these capabilities can streamline line balancing, improve measurement consistency, and free experts to focus on higher-value analysis.

Assignment
The main goal of this thesis is to design, implement, and evaluate a temporal human activity segmentation system that analyses videos to generate a step-by-step sequence of the actions performed.

The challenges include

• Problem understanding: Learn with domain experts to formalize the problem’s challenges, constraints, and dynamics.
• Literature exploration: Review and synthesize recent work to select candidate models, features, and evaluation metrics.
• Planning & design: Define scope; choose methods; decide on datasets (existing or to be collected) and metrics/protocols.
• Implementation: Acquire or build the dataset and implement the methods in a reproducible cloud pipeline.
• Communication: Compile insights, results, and recommendations into clear documentation and a final presentation.

Even if you don’t have experience with everything mentioned above, we still encourage applications from students of all backgrounds and perspectives. Participants will gain hands-on experience and receive regular mentorship and collaboration opportunities throughout the project.

Education and time plan:

Education: Master’s program in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Industrial Analytics
Number of students: 1 - 2
Start date: January 2026
Estimated time needed: 20 weeks
Topics: Artifical Intelligence, VLM, Vid-LLM, Agents, Cloud 

Application

Your application should contain

• CV
• Personal letter
• Copies of grades
• Optional: propose a tentative approach to the problem

Contact persons:

Veeresh Elango (veeresh.elango@scania.com)

Marian van Helmond ()

Applicants will be assessed on a continuous basis until the position is filled. Do not wait until the last date to apply. 

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.    

Nothing is more important than our people. With a company culture that’s based on shared and inclusive core values. We have a supportive community, where everyone has opportunities to grow and succeed.