At the end of the first year, students will be able to choose the topic of their Master's thesis with the assistance of academic coordinators and write the first version of their Master's thesis project proposal. Students will primarily devote the fourth semester to the Master's thesis, working closely with the supervisor, either in an industrial or a higher education institution partner.

The Master's thesis project is a very important part of the Master's degree, including 30 ECTS, which represents 25% of the total of 120 ECTS. Students will have to identify a research hypothesis to be validated or disproved and address some important scientific challenge that will often require the development of a system. It is a mixture of practice in the design, construction and elaboration using scientifically sound methods and evaluation. The thesis work will be considered for submission to scientific conferences.





  1. During the third semester, students submit the project plan (approximately one page) containing the basic information about the project: 

  • Start date
  • Expected end date
  • Supervisor(s)
  • Preliminary project title
  • Tentative research questions or problems to be addressed
  • Global work plan


  1. At the end of the third semester, the preliminary report is due. Students submit a preliminary report containing detailed information about:

  • Introduction
  • Background
  • Research questions or problems to be addressed
  • Preliminary results


  1. The final report is submitted at the end of the fourth semester, and the defense takes place. Students submit the final report to the EMAI Evaluation Committee and perform the oral defense in front of this committee. 


Procedures and requirements 


Evaluation Overview

The student's work is evaluated with regard to the following criteria (weights in parenthesis):
1. Written thesis report

a) Large-scale organisation (15%)

b) Figures and tables (15%)

c) Small-scale writing (15%)

2. Work attitude of the student

a) Assessment of the state of the art (10%)

b) Initiative in problem-solving (20%)

3. Oral thesis presentation

a) Presentation slides (10%)

b) Speech (10%)

c) Free discussion (5%)



Supervisors and Research Topics

Pompeu Fabra University

Supervisors Research Topics
Vincent Adam Probabilistic Modelling, Reinforcement Learning, Optimization
Pablo Arias Martinez Image and Video Restoration, Self-supervised Learning, Bayesian Estimation, Generative Models, Diffusion Models
Coloma Ballester Computer Vision, Multimodal scene understanding from video, Unsupervised learning
Bart Bijnens Cardiovascular Diseases, Clinical Decision Support, Manifold Learning, Multiple Kernel Learning
Miguel Calvo-Fullana Reinforcement Learning, Constrained Learning, Multi-agent, Connected Autonomy, Optimization
Josep Font-Segura Constellation Design for Optical Communications, Error Probability in 6G Wireless Communications, DNA-Based Storage, Deep Learning Information Theory, Signal Processing and Information Theory in Machine Learning
Vicenç Gómez Reinforcement Learning, Automated Planning, Probabilistic Inference, Large Language Models, Social Networks
Gloria Haro Computer Vision, Multimodal analysis, 3D Reconstruction, Sports Video Analysis
Davinia Hernández-Leo Artificial Intelligence in Education, Learning Analytics, Learning Technologies, Human-AI collaboration, Human-Centred Computing
Anders Jonsson Automated Planning, Reinforcement Learning, Exploiting Structure

Jorge Lobo

Symbolic Reasoning, Neuro-symbolic Computation
Rubén Moreno Bote Natural and Artificial Intelligence, Computational Neuroscience, Reinforcement Learning, Decision Making
Gergely Neu Reinforcement Learning, Machine Learning Theory, Sequential Decision making, Online Learning, Statistical Learning Theory
Miquel Oliver Data Analysis and Prediction, Transport System, Blockchain
Narcis Pares HCI, Mixed Reality, Embodied Interaction, Learning, Autism, Heritage
Gemma Piella Medical Image Analysis, Computer Vision for Medical Applications, Explainability, Uncertainty Quantification, Generative models
Manuel Portela Charnejovsky Privacy-preserving data-mining, Geospatial Data Modelling, Responsible Data Sharing Practices
Horacio Saggion Natural Language Processing (NLP) for Good, Text Simplification & Accessibility, Scientific Text Mining, Artificial Creativity and Language Processing and Generation, Natural Language Processing for Sign Languages
Javier Segovia Aguas Automated Planning, Reinforcement Learning, Program Synthesis



Sapienza University

Supervisors Research Topics
Irene Amerini Computer Vision, Fake Detection
Giorgio Grisetti Probabilistic Robotics, SLAM
Luca Iocchi Social Robotics
Domenico Lembo Knowledge Representation Methods for Ontology-based Data access
Francesco Leotta Robotics for Precision Agriculture
Andrea Marrella Automated Planning
Massimo Mecella LLMs for Supporting Software Development and Software Architecture Design, AI in Industry 4.0, AI and BPM - Business Process Management
Roberto Navigli Multilingual Natural Language Processing
Fabrizio Silvestri Deep Neural Networks

Potential supervisors can also be any of the lecturers of the courses attended during the programme.


Radboud University

Supervisors Research Topics
Gunes Acar Privacy, Web Security
Lejla Batina AI for Cryptography, Implementation Attacks
Ileana Buhan AI for Cryptography, Implementation Attacks
Joan Daemen Cryptography
Martha Larson Recommender Systems, Information Retrieval, Multimedia Analysis, Language and Speech Technology
Stjepan Picek AI, Security of AI, AI for Security
Erik Poll System Security
Hanna Schraffenberger Human-computer Interaction

Potential supervisors can also be any of the lecturers for the courses in the programme. Additional topics can be found here.


University of Ljubljana

Supervisors Research Topics
Zoran Bosnić Artificial Intelligence, Machine Learning
Ivan Bratko Artificial intelligence, Machine learning, Knowledge-based systems, Qualitative modelling, Intelligent Robotics
Tomaž Curk Machine Learning, Bioinformatics
Luka Čehovin Zajc Human Computer Interaction, Motion Perception Understanding
Janez Demšar Machine Learning, Data Mining with Emphasis on Data Visualization
Jure Demšar Neuro Informatics, Collective Behaviour
Jana Faganeli Pucer Machine Learning in Environmental Science
Tomaž Hočevar Machine Learning, Algorithms and Data Structures
Matej Kristan  Visual Object Tracking, Detection and Segmentation, Vision for Mobile Robotics
Matjaž Kukar  Machine Learning and Medical Data
Alan Lukežič Computer Vision
Peter Peer Computer Vision, Biometrics
Marko Robnik Šikonja Natural Language Processing, Network Analytics
Aleksander Sadikov Heuristic Research, Medical Decision Support Systems, Eye Tracking
Danijel Skočaj Computer Vision, Machine Learning, Cognitive Robotics
Franc Solina  Computer Vision
Erik Štrumbelj  Probability, Statistics, Machine Learning
Lovro Šubelj  Network Science, Machine Learning with Graphs
Jure Žabkar Artificial Intelligence
Slavko Žitnik Information Retrieval, Information Extraction
Bojan Žunkovič Machine Learning for Quantum
Blaž Zupan Explainable AI, Machine Learning, Data Visualization


Associated Partners


Contact person: Naroa Zurutuza



Fundació Eurecat

Contact person: Joan Mas-Albaigès