📣 Early Contact Recommended: If you’re interested in one of these MSc projects, please get in touch with Prof. Rudolf Mester well before May 1st to receive personal guidance and secure your spot in a suitable project.
Thematic Clusters of MSc Topics
The MSc thesis and preproject topics supervised by Prof. Rudolf Mester are organized into several closely connected thematic clusters within the broader field of Embodied AI. These topics focus on the design, implementation, and evaluation of intelligent systems that physically operate in the world. The projects are often interdisciplinary and involve collaborations with industry and other NTNU departments, especially the Department of Engineering Cybernetics. The main clusters are:
- Autonomous Maritime Systems
- Computer Vision and Perception
- AI in Aquaculture
- Reinforcement Learning and Motion Planning
- Sensor Fusion and Remote Sensing
- Robotics and Embodied Learning Agents
- Fundamental AI and Machine Learning
Structured Overview of MSc Topics
1. Autonomous Maritime Systems
- SLAM for Autonomous Docking (Zeabuz)
- Situation Awareness for Autonomous Ferry
- Maritime Object Tracking with Deep Learning (Zeabuz)
- Adaptive Motion Planning for Small Ships using RL and MPC
- Weather and Sea Condition Estimation from SITAW (Fugro)
- Digital Twin Vision for Ship Hulls (DNV)
- Maritime Object Detection – Sample Selection (Maritime Robotics)
- Instance Segmentation with LiDAR and Cameras (Maritime Robotics)
- Monocular Depth Estimation (Zeabuz)
- AI-Driven Multi-Modal Perception with LiDAR and Stereo Vision
2. Computer Vision and Perception
- Temporal-YOLO: Time-aware object detection in video
- Transformer-based Pattern Inference Under Occlusion (Jotun)
- Point Cloud Generation from Stereo Images (Fugro)
- Bad Weather Vision Systems for Autonomous Driving
- Attention Mechanisms for Perception Enhancement
3. AI in Aquaculture
- 7 projects on AI for Salmon Health Monitoring
- Intelligent Camera-Based Systems for Aquaculture
- Sonar and Video-Based Monitoring of Wild Salmon (NINA)
4. Reinforcement Learning and Motion Planning
- Adaptive Motion Planning for Ships (also listed in Cluster 1)
- Multi-Agent RL for Simulated Autonomous Driving
5. Sensor Fusion and Remote Sensing
- Fusion of LiDAR and Camera for USVs (Maritime Robotics)
- W-Band Radar for Maritime Perception (Fugro)
- Multi-Modal Perception (LiDAR + Stereo)
- Sonar-Video Fusion for Spawning Run Monitoring (NINA)
6. Robotics and Embodied Learning Agents
- LIMO Robot for Autonomous Ground Navigation
- AI-Based Environment Perception for Underwater Robots (AROS project)
- Visual SLAM for Underwater Snake Robots (AROS project)
7. Fundamental AI and Machine Learning
- NeRFs in Motion – Dynamic Scene Representation
- Uncertainty Quantification in Detection and Classification
Supervision Philosophy and Project Organization
Students working under Prof. Rudolf Mester can expect:
- Individualized, regular supervision, typically on a weekly basis.
- Intensive guidance during the preproject and Master’s thesis writing phases.
- A clear philosophy: writing begins on Day 1 to ensure continuity, clarity, and documentation of progress.
- Many projects are embedded in larger research clusters (4–15 students), often part of nationally funded projects (e.g., Norwegian Research Council).
- Projects are often carried out in cooperation with other departments, notably the Department of Engineering Cybernetics (ITK), and with strong ties to industrial partners.
- The overarching research focus is on Embodied AI—developing tangible, intelligent systems such as autonomous ships, underwater robots, self-driving vehicles, and more.
📌 Important Note (April 2025): Students interested in these topics are strongly encouraged to contact Prof. Rudolf Mester directly way before May 1 in order to receive individual guidance and additional information about available projects.