The Master's Thesis

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.

Calendar

Steps

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

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

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