Available Theses-Internships

Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis or Gerhard Weiss):

Machine learning (especially deep learning techniques) have recently found their way to mimic existing artistic styles or judging pictures, paintings for their aesthetic quality. While the inner details of the algorithms are not directly interpretable, a question that arises is whether the algorithms learn something about concepts like “harmony”.

In this thesis you will work with a real artist (that will provide us with enough data) and explore (a) if there is a way to build such a system that will identify whether an artistic synthesis is in harmony or not and (b) whether after having “seen” many examples the system is able to generate new syntheses that are in harmony. We are particularly interested in assessing the characteristics that lead the algorithm to make specific decisions. Symbolic learning (feature extraction, etc.) and deep learning (feature discovery, etc.) techniques will be explored.

Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

Dialogue systems are emerging as a hot application area of deep learning architectures. There are many examples of how deep learning can be applied to either general domain question-answering or to specific domains (e.g. the ubuntu corpus, company customer support). The main goal is that neural network has to model questions & answers and also keep track of the dialogue state. There is already a developed system (based on the VHRED architecture) that for now provides answers based on information retrieval techniques (i.e. the answer that best matches the question).

Your goal in this thesis would be to extend current model by fine-tuning its architecture and give the possibility to the "chatbot" to answer specific questions. There is also the opportunity of working with a specific corpus of customer support dialogues. 

Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

Convolutional neural networks have been extensively and successfully studied and applied to image data. Convolution is a powerful technique from signal processing that in the concept of images is applied by siding a small kernel matrix over all possible positions in the image with the goal of identifying important features. However, convolution (“optical flow”) can be applied to other data (e.g. temporal) usually in 1-dimension and can show how different variables convolve over time.

Given a multivariate (numeric and categorical) dataset spread over discrete time steps, your goal in this thesis would to be to study how 1-dimensional-convolution can be applied to a prediction task (research into how variables can be represented and how convolution windows can be applied) and construct a NN architecture that solves the problem.


Proposed Master (AI or OR) Thesis (contact Dr Stelios Asteriadis):

Transfer learning is an important open issue in the field of machine learning. The exchange of knowledge allows for a better and faster training of new systems using “experiences” acquired through other ones.

We are looking for a student with good programming skills (preferably Python and/or Java) interested in developing their master thesis in this promising and highly rising area in AI. The main objective of the project is to develop a general AI to be applied in data acquired through different sensors during interacting with serious games. The method to be implemented must allow for knowledge sharing between different games, in order to improve the overall experience provided by the interaction. Transfer learning will facilitate the training of a device which uses, for instance, video data for emotion elicitation, using the information acquired using a different device through, e.g., audio or inertial sensor data (how computer vision based emotion recognition can benefit emotion recognition from other sensors).

The outcome of this project will be the implementation of a method to modify game parameters (e.g. difficulty level) to adapt the game to user performance (e.g. emotional state). This thesis will be focused on transfer learning and it won’t start from scratch. Initially, some datasets and analysis algorithms will be provided in order to facilitate the implementation of the system.

Key words: transfer learning, machine learning

Level: Master in AI or OR. Good programming skills (preferably Python and/or Java) and knowledge about machine learning

Recommended literature:

  1. Zhu, Y. Chen, Z. Lu, S. Jialin P., G. R. Xue, Y. Yu, Q. Yang, Heterogeneous Transfer Learning for Image Classification, AAAI, 2011
  2. T. Zhou, S. J. Pan, I. W. Tsang, Y. Yan, Hybrid Heterogeneous Transfer Learning through Deep Learning, Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence


Proposed Bachelor or Master (AI or OR) Thesis (contact Dr Enrique Hortal):

Mobile phones are probably the first device you use every morning and the last one you use before going to bed. It is becoming a “mandatory” gadget, as it can provide us with a huge amount of information from different sensors. The objectives of this project are the following:

  • Integration of a serious learning game, already developed by our research group, in mobile (android and/or iOS) devices making use of touch screen-based interaction
  • Affect analysis using sensors embedded in the mobile device (e.g. gyroscopes and touch screen data analysis). Ready-to-use tools and algorithms, available in our research group, will be provided for data analysis.

Key words: mobile sensors, affect analysis, serious game

Level: Bachelor or Master (AI or OR). Good programming skills (preferably Python and/or Java) and knowledge about machine learning

Recommended literature:

Céline Coutrix and Nadine Mandran. "Identifying emotions expressed by mobile users through 2D surface and 3D motion gestures." In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pp. 311-320. ACM, 2012.


Proposed Bachelor or Master (AI or OR) Thesis (contact Dr Stelios Asteriadis):

Exchanging experiences with our peers during learning is a very important pedagogical technique. The collaboration between learners with different learning profiles and records implies a new student-student relationship (in contrast to the traditional, student-teacher one) where both students benefit from each other (asking one another for information, evaluating one another's ideas, monitoring one another's work, etc.).

This thesis aims at creating a collaborative game where several students can work together using different technologies (i.e. computers and mobile devices). To that end, the student will adapt a serious game, already developed in our group, to be easily used in mobile (Android and/or iOS devices) devices, while, at the same time, sharing goals and performance with peers, in real time. User Experience tests are also expected, following Human-Computer Interaction principles.

Key words: serious games, collaborative games, sharing information

Level: Bachelor or Master (AI or OR). Good programming skills (preferably Python and/or Java) and elementary knowledge about machine learning


Proposed Bachelor or Master (AI or OR) Thesis (contact Dr Enrique Hortal):

Data annotation is a tedious process that usually implies the expenditure of considerable time, effort and resources. Using already recorded data, this thesis will implement a tool to extract key moments from face videos using machine intelligence. These videos come from experiments of people interacting with a serious game and key moments are expected to correspond to key events in the interaction.

The main objective of this project is to implement a simple tool to obtain such video frames which contain useful information about the affective state of the user. To do that, the student will use machine learning in order to differentiate between representative key moments and (more) neutral phases of the game (e.g. using clustering techniques).

To validate this data, manual annotation tools will also be implemented, allowing for humans to extract key moments in people’s expressivity. This project requires good programming skills (preferable Python and/or Java) and some knowledge about machine learning.

Key words: annotation tool, automatic video annotation, machine learning, serious game

Level: Bachelor or Master (AI or OR). Good programming skills (preferably Python and/or Java) and elementary knowledge about machine learning

Recommended literature:

J. Rich and M. Hannafin, (2009). Video annotation tools: Technologies to scaffold, structure, and transform teacher reflection. Journal of Teacher Education, 60, 52-67.

Y. Lin, B. Tseng, and J. R. Smith, “VideoAnnEx: IBM MPEG-7 annotation tool for multimedia indexing and concept learning,” in Proc. Int. Conf. Multimedia & Expo, Baltimore, MD, 2003.


Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

The increasing amounts of text documents (like news items or articles) makes it impossible to follow the trends, events or narratives or the developing storylines. Given a topic detection algorithm applied on a large news corpora dataset (Reuters archive from 1996 and 2015 are available in RAI), the goal of this project is to develop NLP/information retrieval techniques that will facilitate the storyline presentation given the underlying hidden topic structure. Emphasis will be given to the evaluation measures of the results.


Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

Word embeddings is the latest and most effective way to represent documents but has only been extensively applied to English language texts. Recently, embeddings for dutch language were presented (trained on a large corpus). Goal of this thesis is to utilise this representation along with deep learning techniques (like Convolutional Neural Networks) in order to classify a corpus of (dutch) short texts to some predefined categories. 


Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

Graduating attributes (or competences) describe the sets of values that students should develop by the end of their studies. Based on the courses content and students’ development, in this project you will explore different techniques (tensor decomposition, matrix factorization, word2vec, etc.)  in order to build a course recommender system that will suggest students’ courses that will improve either their average competence profile or a specific competence.



Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

Graduate student profiles can be described by many attributes: grades, courses curriculum or even hidden dimensions (like their competences). Similarly, job advertisements can be represented by sets of values that should match those of students’ profiles. Goal of this thesis is to build a reciprocal recommender system that will match students to jobs (and vice versa). Evaluation measures of the algorithm and the overall proposed matching will also be explored. 


Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

Online learning through Massive Open Online Courses (MOOCs) is an emerging education technology area with increasing demands. However, it is found that out of the many thousands of participants enrolled in various MOOC courses, the completion rate for most courses is below 13%. There is not much knowledge yet on the profiling of people taking MOOCs, in order to predict dropout rates. Goal of this thesis is to study a MOOC dataset (already available) and identify or predict dropout probabilities based on user behavior characteristics.

Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

On-line social networks have become a massive communication and information channel for users world-wide. Twitter is a means used by many people in order to express their opinions, complaints, thoughts, etc. for almost every topic. Despite many efforts, there is no clear or robust way to evaluate this kind of data yet (e.g. if a specific tweet corresponds to reality or not or if it corresponds to an accurate review).

Goal of this thesis is to pick a topic (of your interest, otherwise there is already an idea), collect relevant to this topic tweets (based on Twitter streaming API) and then explore or develop methods from literature that can be used to extract useful information. Emphasis will be given to the evaluation of these techniques.

Proposed Bachelor/Master Thesis (contact Gerasimos (Jerry) Spanakis):

Airport congestion and scarce capacity at popular airports are rising problems with no straight-forward solutions till now. An airport slot is a right granted by an airport owner which allows an airline to schedule a landing or departure during a specific time period. Allocated slots may have a commercial value and can be traded between airlines.

Goal of this thesis is to expand an already implemented auction-based system for airport slots in order to further improve the allocation of slots according to specific criteria (profit maximization of airlines, airport utilization, etc.). Dynamic pricing techniques can also be explored as well as airline behavior/negotiation models.

Proposed Master Internship / Thesis (contact Gerhard Weiss):

In close cooperation with and co-supervised by:
         Marco Das, MD, PhD, MBA, Head of CT Department
         Department of Radiology, Maastricht University Medical Centre (MUMC)

The improvement of workflows is crucial for the efficiency and competitiveness of companies and any other kind of organizational units. This internship/thesis is about workflow improvement in hospitals. Specifically, and in cooperation with MUMC, it is about improving the current workflow from clinical request to the final report of a patient. This workflow is complex and requires multiple tasks to be fulfilled with many manual tasks from different  employees (administration, CT technician, radiologist) as well as multiple different computer systems (Hospital Information System SAP, Administration tasks Qdoc, CT scanner software, reporting in AGFA Pacs). In its current form this process is inefficient and even may lead to unsatisfying results for the patient (increased waiting time, wrong protocol, overlooked pathology due to insufficient imaging).

The task is to develop a software for an efficient workflow, which combines necessary tasks in terms of administration, as well as optimal patient routing and planning and decision making at which scanner with which protocol the patient has to be scanned.  The ultimate goal is to have the final report of a patient with the optimal imaging in the shortest amount of time.

Proposed Bachelor Thesis / Internship (contact Kirill Tumanov):

In this thesis project you will be exploring how to design, build and evaluate a Hidden Markov Model (HMM), applied to brain signal analysis. Markovian approach assumes that there is a certain state regularity observed in the analized data. But what exactly is this pattern? So far HMMs were extremely successful for instance in speech and handwriting recognition. It has also been found useful in bioinformatics and brain signal temporal analysis.

At the moment a standard Support Vector Machine (SVM) classification is used at UM when working with functional Near-InfraRed Spectroscopy (fNIRS) system for brain recording. SVM will be a banchmark for you to test the designed HMM performance against. Recent research indicated a high potential of HMM to replace SVM in this domain. You will be able to test if this is the case, while deepening your knowledge in Markovian approaches in general and the HMM in particular.

Proposed Master Internship or Thesis in RAI, in collaboration with Qwiek (http://qwiek.eu/) (contact Stylianos (Stelios) Asteriadis, Gerhard Weiss, Rico Möckel ):

The Qwiek.play is a gaming computer for elderly in care homes. The Qwiek.play uses a combination of television, tablet (iPad), RGB camera and a user centered interface to stimulated elderly in a playful, attractive but mainly active way. Games are especially designed to fit their interest and are focuses on their personal perception. Currently we are using the RGB camera to detect motion and face detection (using OpenCV), this works well for the current games. But, we believe that we can get a lot more out of this RGB camera without switching to an expensive 3D camera (and this is why we need you). For instance, if we make the camera more intelligent, we would be able to detect patterns. This can be the detection of simple events like; counting how many people stand in front of the system, or how many people have passed by today or slightly more advanced: detect gestures like waving, raised hands or even a throwing gesture. Your task will be to analyze the camera feed and detect these events (and preferably come up with a lot more).

Step two of the project is more about an user adaptive interface. What do we mean by this? The patterns, which we have stated above, can be used as input for the system to respond “intelligent” in certain situations. But to be truly “intelligent” the system needs to determine the kind of “mood” a user is in. Is he/she laughing or actually being annoyed or bored. Being able to determine these events through image processing, application usage data or sound and let the application respond to this accordingly, would be a very valuable addition to the product. The end goal would be a system which is able to measure its own user interest and make sure it keeps itself interesting for a specific user.

Proposed Master Internship or Thesis in RAI, in collaboration with Qwiek (http://qwiek.eu/) (contact Stylianos (Stelios) Asteriadis, Gerhard Weiss, Rico Möckel ):

All smartphones which are being sold today are equipped with a 9DOF sensor. A 9DOF is (mostly) a 3-axis accelerometer combined with a 3-axis gyroscope and a 3-axis magnetometer (compass). The combination of these sensors are, in theory, able to detect accurate 3D movement of an object in space. Knowing the 3D movement/orientation of an object could be interesting for a variety of applications (for example controlling a drone), but we the area that we are very interested in is measuring accurate body movement (when the sensor is attached to a limb).

Why? Therapist are very interested in analysing the development of a revalidation process. They can measure the progress (or deterioration) and check whether clients are performing a task correctly. Furthermore we can also use the data from the sensor to control training games (serious gaming).

So what are we looking for? To achieve this accurate measurement we need to develop the correct algorithm and noise reduction. You won’t start from scratch! There are a lot of sample projects online and we have made some fairly good progress ourselves. A successful project outcome would be a system which is able to detect reliable body movement within a 3D space and can learn to detect a specific exercise coming from a wide variety of people (with different body dimensions) and give insights in the quality of the movement.

Proposed Master Thesis or Internship in RAI (contact Stylianos (Stelios) Asteriadis): This project will focus on how we can effectively use one or more modalities (e.g. visual, wearable sensors, etc.) in order to map emotions expressed through human bodies on manifold spaces. The impact of this work can span from Computer Graphics to Ambient Assisted Living environments. Ready-to-use or new datasets will be used for the purposes of this work.

Proposed Master Thesis or Internship in RAI (contact Stylianos (Stelios) Asteriadis): The proposed work will focus on the development of cutting-edge interaction schemes in the brand new area of interaction between humans and robots, in non-verbal, contactless manners, just through visual cues conveying affective messages (emotions, cognition). Possible applications lay in the areas of medicine, education, game-play, etc.


Proposed Master Thesis or Internship in RAI (contact Stylianos (Stelios) Asteriadis): This work will deal with robot navigation in unknown, indoor environmetns. In particular, the recent notion of mid-level discriminative patches (see work 'What makes Paris look like Paris') will be used and extended for seeing what separates one room from another and, thus, assist a robot understand where it is. Research will also be conducted in using spatial and image-based information for object recognition, opening new paths to robot-based assistive environments.

Proposed Bachelor/Master Thesis in RAI (contact Gerasimos (Jerry) Spanakis): Moneyball is a book (later turned into a film) that describes a team’s analytical, evidence-based, sabermetric approach to assembling a competitive baseball team. Nevertheless, not many such scientific approaches have been applied to basketball (or other sports), despite all statistics being available (for example, see accumulated statistics for a basketball player in Euroleague). There are many data available like number of points, free throw percentage, turnovers, etc, organized per season. This thesis requires the following steps:
(1) Choose a sport, collect & assemble the data (you might need to implement wrapper for that to scan resources like the euroleague.net).
(2) Label accordingly the players and detect career paths.
(3) Apply state-of-the-art (or new!) machine learning algorithms (SVM, decision trees, etc) to predict career paths.

Proposed Bachelor/Master Thesis in RAI (contact Gerasimos (Jerry) Spanakis): You maybe familiar with university rankings (there are dozens of them available with different criteria and of course different results!). But what do people think about universities and what does the Web think? In this thesis we will explore techniques to take advantage of Google Trends tool in order to identify university rankings (we can limit the study in dutch universities for start). Google trends do not offer specific data (only relative) but we can exploit these data (curves, differences, per-year data) in order to build a university ranking measure based on web search results. Your steps in these thesis are: 

  • Select a sample of universities and collect data from Google trends
  • Select appropriate tools from the machine learning pool to build a measure of ranking.

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): Tennis is a popular worldwide spectator sport with many international competitions all over the year. Predicting Tennis game result is challenging task. It is the goal of this thesis to develop a system which can predict the result of a Tennis game between two players given several features like the players' ranking, their head to head result, their performance on that specific tournament, their performance on that type of courts, etc. A full dataset for all results of ATP tennis tournaments is available since 1968.

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): Social media has made a big impact on the tourism industry. Tourists are more likely to share their personal experiences of a particular touristic site scene using Social Media. Tracking tourists’ footprints supports the tourism industry with more statistics and other information regarding tourism demand. The goal of this thesis is to utilize both textual contents and geo-location information of Tweets posted by tourists visiting The Netherlands to provide a near real scenario for the tourists’ travel route made during their stay in The Netherlands. Moreover, it is required to induce some useful statistics regarding the top touristic attractions in The Netherlands and their peak season.

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): Social media accounts are valuable for hackers for spreading phishing links, malware and spam. Furthermore, some
people deliberately hack an acquaintance to damage his or her image. This aim of this thesis is to develop a runtime classi cation system for detecting hacked Twitter accounts. The state-Of-The-Arts models are mainly based on features associated with behavioural change such as changes in language, source, URLs, retweets, frequency and time. In this thesis we want to investigate a new approach which is based on differences in writing style. A sudden change in the writing style or in the topics being mentioned by the author of the account are important indicators for the threat of a hacked account.

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): Huge amount of raw data is being collected from different sources every day. By aggregating this data we may discover weird and unexpected behaviors like positive or negative peaks. These anomalies are missing the proper semantics. For example, traffic data provides average journey time, speed and traffic flow information for highways. By aggregating this data we may find some unexpected traffic jam at certain place in a certain period of time. It is the goal of this thesis to analyse social media (Twitter) data to discover the causes of these anomalies which may appear to be a festival or an accident reported at this location on this specific time. 

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): The presence of militant group Islamic State of Iraq and Syria (ISIS) is growing. Terrorist attacks in Europe, an incoming stream of refugees in the south of the continent and propaganda videos spread through social media are a number of the reasons Europe is getting socially involved in the Middle-Eastern war. It might seem that the Netherlands could become a target of the organisation too. The goal of this thesis is to discover the potential of a terroristic threat by analyzing the sentiment of Dutch Tweets discussing ISIS activities and crimes. Showing support, satisfaction or happiness to ISIS crimes could be considered an alarm for security agencies that requires further investigations.

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib and Gerasimos (Jerry) Spanakis): User generated content (UGC) such as the text in Twitter messages is notoriously varied in content and composition, often containing ungrammatical sentence structures, non-standard words and domain-specific entities. Accuracy declines have been observed in many NLP tasks over UGC, motivating the need for methods which normalise the content prior to the application of NLP tools to the data. This thesis is aiming to normalise non-standard words in English Twitter messages to their canonical forms. In this, we aim to correct non-standard spellings (e.g., toook for took), expand informal abbreviations (e.g., tmrw for tomorrow), and normalise phonetic substitutions (e.g., 4eva forforever).

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib and Gerasimos (Jerry) Spanakis): Microposts (like Tweets) are a highly popular medium to share facts, opinions or emotions. They are an invaluable wealth of data, ready to be mined for training predictive models. The task of the thesis is to automatically recognise entities and their types from English microposts, and link them to the corresponding English DBpedia 2014 resources (if the resources exist) or NIL identifiers. You have to automatically extract expressions that are formed by discrete (and typically short) sequences of words (e.g., Obama, London, Rakuten) and recognise their types (e.g., Person, Location, Organisation) from a collection of microposts. In the linking stage, the aim is to disambiguate the spotted entity to the corresponding DBpedia resource, or to a NIL reference if the spotted named entity does not match any resource in DBpedia.

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): When does citizenship provide a boost to migrant integration? A fast-track to citizenship can maximize the potential for settlement success of migrants, though too short a pathway can disincentivize integration. While there is much talk among politicians about citizenship being either a reward, or an instrument, of immigrant integration, we actually know relatively little about how this works in practice. It is the aim of this thesis to develop a system which predicts if an immigrant would be able to integrate and get the Dutch citizenship or not based on his/her registration information over 4 or 5 years.  

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): People normally tend to post on social media about their interests. Given the posts, likes, and friends of a social media profile (Twitter or Facebook), it is required to predict the basic information of the profile holder like Address, Job, Age and Gender.

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib and Rico Möckel): Running experiments using multiple robots requires a robot tracking system to monitor each individual robot behavior in the experiments. It is required to design and implement a framework which uses cameras to monitor and track mini-robots.

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): Development of Information Access technologies based on techniques of Information Retrieval, Natural Language Processing, and Database Management becomes increasingly more important for many applications, (e.g., providing effective access to Web resources and text archives, and analyzing big data obtained from various kinds of sensors). It is indispensable for developing such technologies to experimentally evaluate them by using test collections constructed under collaborations of many researchers. Over the 15 years, NTCIR has been formulating the infrastructure for the evaluation, and contributing to development of the Information Access technologies. A total of 70 "evaluation tasks" have been organized, attracting over 880 participant research groups worldwide so far. Furthermore, over 3,700 research groups have signed up to use the NTCIR test collections in their research. Consequently, NTCIR has been the major forum for researchers to intensively discuss the evaluation methodology of emerging information access technologies. The thirteenth NTCIR, NTCIR-13, now calls for task participation of anyone interested in research on information access technologies and their evaluation, such as retrieval from a large amount of document collections, question answering and natural language processing. We welcome students, young researchers, professors who supervise students, researchers working for a company, and anyone who is interested in informatics.

Full description of the available tasks can be found here: http://research.nii.ac.jp/ntcir/ntcir-13/NTCIR13CFPFlyererEn.pdf

Proposed Bachelor/Master Thesis in RAI (contact Mena Habib): SemEval (Semantic Evaluation) is an ongoing series of evaluations of computational semantic analysis systems, organized under the umbrella of SIGLEX, the Special Interest Group on the Lexicon of the Association for Computational Linguistics. SemEval has evolved from the SensEval word sense disambiguation evaluation series. The SemEval wikipedia entry and the ACL SemEval Wiki provide a more detailed historical overview. 

Full description of the available tasks can be found here: http://alt.qcri.org/semeval2017/index.php?id=tasks