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Master Projects

Possible assignments

Philips HUE Product Evolution Using Stream Mining of Customer Journey

Philips HUE is a connected personal lighting system. It is controlled by a range of apps and smart home devices.

To acquire Philips HUE, one starts with a starter kit that consists of a few lamps and a bridge. Subsequently, consumers decide to expand their system with additional lamps or/and physical sensors. About 50 lamps can be controlled in one system.

An example of HUE system is seen in the Figure below. It consists of a bridge, three color lamps and a dimmer switch.

Every consumer chooses a device to interact with the lights. By default, all consumers start with HUE or third-party app. There are also options in the HUE app to create routines to be able to control the lights automatically. For instance, one can create a wakeup routine so that the lights in the bedroom go on naturally in the morning. HUE can also be controlled by Philips physical sensors (motion sensor, tap, dimmer switch), voice control and other third party smart home devices. Amazon Echo, Google Home, Eneco Toon, Homekit are some of smart home devices that are linked to HUE. In addition, traditional wall switch can also be used to control the lights. For further information see Philips Lighting website.

The master thesis focusses on developing a process mining model to understand product evolution of consumers in their journey and identify the paths that contribute to a high Customer Lifetime Value (CLV). Moreover, the thesis will also explore data mining techniques that can be applied on the outcome of process mining model.

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Process mining in Logistics - 3D Visualization and Scalable Process Mining on Big Event Data (2 Topics)

Vanderlande is the global market leader for value-added logistic process automation at airports and in the parcel market. The company is also a leading supplier of process automation solutions for warehouses. Some figures:

  • Vanderlande’s baggage handling systems move 3.7 billion pieces of luggage around the world per year.
  • Our systems are active in 600 airports including 13 of the world’s top 20.
  • More than 39 million parcels are sorted by its systems every day, which have been installed for the world’s leading parcel companies.
  • Many of the largest global e-commerce players and distribution firms have confidence in Vanderlande’s efficient and reliable solutions.

Vanderlande focuses on the optimization of its customers’ business processes and competitive positions. Through close cooperation, we strive for the improvement of our customers’ operational activities and the expansion of their logistical achievements.

For Vanderlande, it is critical that we have state-of-the-art techniques to analyze and optimize our customers’ logistics processes. Reasons are (a) the constant increasing size and complexity of our material handling solutions, (b) growing complexity of our software solutions, covering larger parts of our customers’ business processes, and © the demand for more advanced service offerings, covering logistics and business services. We believe that process mining is of high value for Vanderlande. Therefore, we work with the Eindhoven University of Technology on making process mining fit for analyzing logistics processes. In this context, we offer graduation projects on process mining and the application in our business.

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Want to win?

Win the Process Discovery Contest (PDC) 2018!

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When Portfolio Management meets Process Mining Challenges and Opportunities

FLIGHTMAP is Bicore’s flagship software solution for portfolio management. Since its launch in 2010, a growing group of international clients, such as DAF, Océ, and Fokker, have implemented FLIGHTMAP. With this tooling, they can perform roadmapping, budget and resource planning, scenario analysis, planning and tracking, and more. More information about FLIGHTMAP is available via www.flightmap.com. The figure above shows a screenshot of the tool obtained after the portfolio analysis

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Data Science: Developing a Self-Standing Dynamic reporting tool

A huge amount of (transaction) data is generated on a daily basis in ASML Development and Engineering department. The data is scattered in different sources. The challenge would be extracting data from relevant sources and creating a self-standing dynamic reporting tool (dashboard) demonstrating performance of (Supplier Quality) Engineers in different granularity levels (Department, Section, Individual) based on a set of pre-defined KPIs.

Are you a master student in Software Engineering (Data Science) with a passion on real-life data challenges? Then we are looking for you!

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Real-Time Model Discovery of the Service Order Process Using Stream Process Mining

Kropman Installatietechniek is a Dutch company established in 1934 and has become one of the leading companies of the Dutch installation industry. With about 800 employees, 12 regional locations and an annual turnover of more than 100 million Euro, Kropman is an integral service provider with a multidisciplinary approach. Kropman is mainly active in office buildings, health care and industry. It offers design, construction and maintenance in the field of facility installations. Kropman also has a separate business for process installations and cleanrooms: Kropman Contamination Control. The maintenance (services) is a fast growing business line. The order process is fully supported within an ERP environment. The service order process is not a trouble-free process: the process takes too long and flows more often than necessary. The company aims at increasing the throughput of the SO process and decreasing the amount of process deviations by applying process mining and data mining techniques.

To have a better overview of the process, Kropman is aiming at:

  • Exposing bottlenecks happening in the SO process
  • Detecting deviations from the supposed model in the real time they are happening using stream process mining techniques

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Procedure for Master Projects

  • Within the AIS group, we offer Master projects in several different areas and also on concrete topics. We then tailor the Master project assignments for each individual student, with that student’s skills in mind. To create an individual assignment, you have to find and commit to a supervisor who helps you in this process.
  • If you already know with which supervisor/on which topic you want to graduate, contact the potential supervisor of your choice directly, and as early as possible (at the end of the first year, after you have obtained 40 to 50 credits)
  • If you first want to get an overview on available projects and supervisors, please contact Dirk Fahland. He can direct you to a potential supervisor in your area of interest, and you then talk with the potential about possible Master projects.
  • At some point the student has to commit to a particular supervisor. Only then an actual assignment can be defined, either internal or external. In particular external assignments must be discussed and defined together with the supervisor to ensure that the defined assignment fits the student, the company, and the study program.

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Research Lines

Assignments for master projects typically fall in one of the main three research lines of AIS:

Processes

The research group distinguishes itself in the Information Systems discipline by its fundamental focus on modelling, understanding, analyzing, and improving processes. Essentially, every time two or more activities are performed to reach a certain goal, fundamental principles of processes apply. Processes take place on the level of individual actors, groups of actors, entire organizations, and networks of organizations. Processes, in one form or another, can be seen everywhere:

In traditional workflow management settings, the idea behind a process is that there is a single notion of a “case” flowing through a “process” according to a pre-defined route, i.e. a “process model”. However, the notion of processes and the principles behind them are much broader. In many situations, processes are not explicitly defined (there is no procedure for a customer clicking through a website) or are highly flexible (typically in knowledge intensive processes such as designing products or deciding about visa and immigration). Also, many processes have interactions with other processes: for example, there are many interlinked processes behind every patient in a hospital or behind the supply chain of any multi-national manufacturer. There is a growing concern within organizations, governments, and society as a whole that processes need to be governed properly and efficiently. The availability of large amounts of data on the one hand and a fundamental understanding of the process notion on the other shape the opportunity for researchers in our group to contribute to this societal challenge.

Background: Business Process Management

Within organizations, the management of processes has been an important topic since the introduction of conveyor belts in the early 1920’s. From 2000, business process management is the research field focusing on agility in organizations and continuous (business) process improvement through a BPM life-cycle of designing, modelling, execution, monitoring and optimizing processes.

Lately, there is growing attention in the field of business process management for the embedding of process analytics into (process aware) information systems, i.e. BPM provides the context in which our analytics are being developed.

Fundamental to the research group at the Eindhoven University of Technology is the choice for Petri nets as the language to precisely describe process dynamics also in complex settings at a foundational level. The choice for this language is what distinguishes our research group from research groups in more industrial engineering oriented information systems groups.

Process Analytics

One of the foundations of computer science today is data. The omnipresence of increasingly large volumes of data has become a key driver for many innovations and new research directions in computer science. Specifically in information systems, data - and the analytics developed on top of this data - have transformed the field from expert-driven to evidence-based, which in turn massively broadens the applicability of results to more and larger contexts. Many advanced process analysis tools and techniques exist today in over 25 commercial packages that were developed in the AIS group over the last 15 years.

The research in the our group continues to expand outward from a “classical” situation of data with clear case notions in the context of explicitly structured processes to a broad, multi-faceted field, where processes are less structured or consist of many interacting artifacts and where case notions in data become more fluid or are complex, multi-dimensional networks.

The figure above shows this research field of process analytics.

Impact and Societal Relevance

When selecting a Master project it is advisable to consider the track record of the research group supervising the project. Therefore, we briefly discuss the impact and societal relevant of AIS’s research.

The work of the AIS group is world renowned, especially in the fields of

  1. the modeling and analysis of workflow processes (cf. workflow nets and the seminal soundness notion),
  2. workflow patterns (the DAPD paper on the workflow patterns is the most cited paper in the BPM domain and the Workflow Patterns web site is the most visited web site on workflow management over the last decade), and
  3. process mining (e.g., we established an international process mining community).

The impact of our work is reflected by the many citations of the publications of the AIS group. For example, Wil van der Aalst is the highest ranked European computer scientist based on Google Scholar. His work has been cited more than 63,000 times and his Hirsch Index is 120. During the last evaluation of all computer science groups in the Netherlands, the AIS group got the highest marks possible: 5-5-5-5-5 (i.e., a perfect score). The workflow patterns have had a very positive effect on commercial WFM/BPM products. Today, the patterns are widely used to describe workflow functionality in a language/system-independent manner. In addition, the patterns are also highly visible. The Wokflow Patterns web site has been one of the most visited web sites in the field of BPM averaging more than 300 unique visitors per working day over the last decade. Several vendors changed their tools to support more patterns and some have provided wizards based on the patterns. For example, IBM recently added a wizard-like functionality to their WebSphere product inspired by the patterns. Also standardization efforts were influenced by the patterns, see for example BPMN.

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Staff involved

Wil van der Aalst

Position: HGL
Room: MF 7.064
Tel (internal): 4295
Projects: Core, DeLiBiDa, DSC/e & NWO Graduate Program, Phlips Flagship, Process Mining in Logistics, RISE BPM
Courses:
Links: Personal home page, Google scholar page, Scopus page, ORCID page, TU/e employee page, DSC/e
Prof.dr.ir. Wil van der Aalst is a full professor of the Process and Data Science (PADS) group at the RWTH in Aachen (Germany) and a part-time professor in the AIS group. His personal research interests include process mining, business process management, workflow management, Petri nets, process modeling, and process analysis.

Joos Buijs

Position: UD
Room: MF 7.062
Tel (internal): 3661
Projects: CoseLoG, EDSA, Phlips Flagship, RISE BPM, TACTICS
Courses: 2IMI20
Links: Personal home page, Google scholar page, Scopus page, ORCID page, TU/e employee page, DSC/e
Joos Buijs' current research interests include Process mining in healthcare and Learning analytics. Next to these research topics Joos is also involved in MOOC creation. Related to the learning analytics of course, we also create MOOCs on the topic of process mining. There is the Coursera MOOC "Process Mining: Data Science in Action". And on July 11, 2016 the first session of the FutureLearn MOOC "Process mining with ProM" will launch, a hands-on MOOC where you learn how you can apply process mining on your own data!

Boudewijn van Dongen

Position: UHD
Room: MF 7.103
Tel (internal): 2181
Projects: 3TU.BSR, DeLiBiDa, Process Mining in Logistics
Courses: 2IMC92, 2IMC97, 2IMI05, 2IMI30, JBG010, Big Data Honors Track
Links: Google scholar page, Scopus page, ORCID page, TU/e employee page
Boudewijn’s research focusses on conformance checking. Conformance checking is considered to be anything where observed behavior, needs to be related to already modeled behavior. Conformance checking is embedded in the larger contexts of Business Process Management and Process Mining. Boudewijn aims to develop techniques and tools to analyze databases and logs of large-scale information systems for the purpose of detecting, isolating, diagnosing and predicting misconformance in the business processes supported by these systems. The notion of alignments play a seminal role in conformance checking and the AIS group is world-leading in the definition of alignments for various types of observed behavior and for various modelling languages.

Massimiliano de Leoni

Position: UD
Room: MF 7.059
Tel (internal): 8430
Projects: Core
Courses: 2IIC0, 2IHI10, 2IMI35, 2IOC0
Links: Personal home page, Google scholar page, Scopus page, ORCID page, TU/e employee page
Dr. Massimiliano de Leoni is assistant professor at the AIS group. His research focuses in the areas of Process-aware Information Systems and Business Process Management, predominantly on multi-perspective process mining, process-aware decision support systems as well as on visualization techniques for business process management and analysis. He has a genuine interest in the practical applications of his research in real-life settings, which led him to concretely develop his ideas in term of software tools and apply them with a large number of organizations world-wide.

Dirk Fahland

Position: UD
Room: MF 7.066
Tel (internal): 4804
Projects: BOSS, Process Mining in Logistics
Courses: 2IIC0, 2IHI10, 2IMC92, 2IMC97, 2IMI10, 2IOC0, JBG030, JBG040, JBG050
Links: Personal home page, Google scholar page, Scopus page, TU/e employee page
Dirk is Assistant Professor (UD) in the AIS group. He completed his PhD with summa cum laude at Humboldt-Univeristät zu Berlin and Eindhoven University of Technology in 2010. His research interests include distributed processes and systems built from distributed components for which he investigates modeling systems (using process modeling languages, Petri nets, or scenario-based techniques), analyzing systems for errors or misconformances (through verification or simulation), and process mining/specification mining techniques for discovering system models from event logs. He particularly focuses on distributed system with multi-instance characteristics and their synchronizing and interacting behaviors. Dirk published his research results in over 40 articles at international conferences and journals and implemented them in a number of software tools.

Marwan Hassani

Position: UD
Room: MF 7.097A
Tel (internal): 3887
Projects:
Courses: 2IAB0, 2IIC0, 2IHI10, Big Data Honors Track, JM0210
Links: Personal home page, Google scholar page, Scopus page, ORCID page, TU/e employee page
Dr. Marwan Hassani is assistant professor at the AIS group. His research interests include streaming process mining, stream data mining, sequential pattern mining of multiple streams, efficient anytime clustering of big data streams and exploration of evolving graph data. Marwan received his PhD (2015) from RWTH Aachen University. He coauthored more than 45 scientific publications and serves on several program committees.

Farideh Heidari

Position: UD
Room: MF 7.119
Tel (internal): 2257
Projects:
Courses:
Links: Personal home page, Google scholar page, Scopus page, ORCID page, TU/e employee page
Farideh has a multi-disciplinary educational and professional background: math and physics, mechanical and industrial engineering, and PhD in information systems. Her unique blend of experiences in academic and industrial areas has made Farideh a person with an original point of view and gave Farideh a broad perspective to life and a goal to aim. This enables Farideh to bring industry and research together to provide organisations with effective solutions to their businesses.

Wim Nuijten

Position: HGL
Room: Flex
Tel (internal): 3877 (2733)
Projects: DAIPEX
Courses:
Links: Scopus page, TU/e employee page
Prof. Wim Nuijten is a part-time professor at the AIS group focusing on Intelligent Information Systems. He is an expert in the area of constraint programming and advanced planning and scheduling. Currently, he is working for Quintiq, a company leading in the area of advanced planning and scheduling. Before, he worked within IBM and ILOG.

Hajo Reijers

Position: HGL
Room: Flex
Tel (internal): 3629
Projects: CoseLoG, TACTICS
Courses: 2IMI00
Links: Personal home page, Google scholar page, Scopus page, ORCID page, TU/e employee page
Prof.dr.ir. Hajo Reijers is a part-time, full professor of Information Systems at the Technische Universiteit Eindhoven (TU/e). He is also a full professor in Business Informatics at VU University Amsterdam. He is also affiliated to the TiasNimbas Business School, where he is involved as one of the core lecturers in the Executive Master of Operations and Supply Chain Excellence (MOS) program. Hajo Reijers is one of the founders of the Business Process Management Forum, a Dutch platform for the development and exchange of knowledge between industry and academia. Hajo Reijers received a PhD degree in Computer Science (2002), an MSc in Computer Science (1994), and an MSc in Technology and Society (cum laude) (1994), all from TU/e. Hajo Reijers wrote his PhD thesis while he was a manager with Deloitte. Previously, he also worked for Bakkenist Management Consultants and Accenture. As a consultant, he has been involved in various reengineering projects and workflow system implementations, particularly for governmental agencies and organizations offering financial services. From 2012 to 2014, Hajo Reijers headed the BPM R&D group of Perceptive Software. The focus of Hajo Reijers' academic research is on business process redesign, workflow management, conceptual modeling, process mining, and simulation. On these topics, he published over 150 scientific papers, chapters in edited books, and articles in professional journals.

Natalia Sidorova

Position: UD
Room: MF 7.105
Tel (internal): 3705
Projects: Phlips Flagship
Courses: 2IAB0, 2IMI15, 2IMI35, DASU20
Links: Personal home page, Google scholar page, Scopus page, TU/e employee page
Dr. Natalia Sidorova is assistant professor at the AIS group. She actively works on topics related to process modeling and verification. The application domains include business processes and distributed systems. She has published more than 70 conference and journal papers. She is active in the Health and Wellbeing Action Line of EIT ICT Labs, taking lead of projects towards the development of innovative services for disease prevention making use of modern sensor technologies together with mining, conformance analysis, prediction and recommendation techniques.

Example projects

Bram in 't Groen

VDSEIR - A graphical layer on top of the Octopus toolset

Description

In his work, Bram in 't Groen introduces a graphical representation for DSEIR (a language used in the Octopus toolset for designing embedded systems) called Visual DSEIR (VDSEIR). By using VDSEIR, users of the toolset can create specifications in DSEIR by means of creating graphical models, removing the need for those users to know how to program in the Octopus API. Bram in 't Groen provides a model transformation from VDSEIR to DSEIR that makes use of an intermediate generator model and a parser that is automatically generated from an annotated JavaCC grammar. The graphical representation for DSEIR consists of several perspectives and it contains a special form of syntactic sugar, namely hierarchy. It is possible to create hierarchical models in the graphical representation without having support for hierarchy in the original DSEIR language, because these hierarchical models can be translated into non-hierarchical DSEIR models. This way, additional expressiveness is created for the user, without modifying the underlying toolset.

Type

AIS / External / ESI

Borana Luka

Model merging in the context of configurable process models

Description

While the role of business process models in the operation of modern organizations becomes more and more prominent, configurable process models have recently emerged as an approach that can facilitate their reuse, thereby helping to reduce costs and effort. Configurable models incorporate the behavior of several model variants into one model, which can be configured and individualized as necessary. The creation of configurable models is a complicated process, and tool support for it is in its early steps. In her thesis, Borana Luka evaluates two existing approaches to process model merging which are supported by tools and test an approach to model merging based on the similarity between models. Borana’s work resulted in a paper presented in the 2011 International Workshop on Process Model Collections.

Type

AIS / Internal / CoSeLog project involving 10 municpalities

Links
Staff involved

Cosmina Cristina Niculae

Guided configuration of industry reference models

Description

Configurable process models are compact representations of process families, capturing both the similarities and differences of business processes and further allowing for the individualization of such processes in line with particular requirements. Such a representation of business processes can be adopted in the consultancy sector and especially in the ERP market, as ERP systems represent general solutions applicable for a range of industries and need further configuration before being implemented to particular organizations. Configurable process models can potentially bring several benefits when used in practice, such as faster delivery times in project implementations or standardization of business processes. Cosmina Niculae conducted her project within To-Increase B.V., a company that specializes in ERP implementations. She developed an approach to make configuration much easier, implemented it, and tested it on real-life cases within To-Increase.

Type

AIS / External / To-Increase

Links
Staff involved

Dennis Schunselaar

Configurable Declare

Description

Declarative languages are becoming more popular for modeling business processes with a high degree of variability. Unlike procedural languages, where the models define what is to be done, a declarative model specifies what behavior is not allowed, using constraints on process events. In his thesis, Dennis Schunselaar studies how to support configurability in such a declarative setting. He takes Declare as an example of a declarative process modeling language and introduces Configurable Declare. Configurability is achieved by using configuration options for event hiding and constraint omission. He illustrated our approach using a case study, based on process models of ten Dutch municipalities. A Configurable Declare model is constructed supporting the variations within these municipalities.

Type

AIS / Internal

Links
Staff involved

Erik Nooijen

Artifact-Centric Process Analysis, Process discovery in ERP systems

Description

In his thesis, Erik Nooijen developed an automated technique for discovering process models from enterprise resource planning (ERP) systems. In such systems, several different processes interact together to maintain the resources of a business, where all information about the business resources are stored in a very large relational database. The challenge for discovering processes from ERP system data, is to identify from arbitrary tables how many different processes exist in the system, to extract event data for each instance of each process in the system. Erik Nooijen identified a number of data mining techniques that can solve these challenges and integrated them in a software tool, so that he can automatically extract for a process of the ERP system an event log containing all events of that process. Then classical process discovery techniques allow to show the different process models of the system. Erik conducted his project within Sligro where he is actively using his software to improve the company's processes. The thesis resulted in a workshop paper presented at the International Conference on Business Process Management 2012 in Tallinn, Estonia.

Type

AIS / External / Sligro

Links
Staff involved

Irina-Maria Ailenei

Process mining tools: A comparative analysis

Description

In her thesis, Irina-Maria Ailenei proposes an evaluation framework that is used to assess the strengths and the weaknesses of process mining tools. She applied the framework in practice for evaluating four process mining systems: ARIS PPM, Flow, Futura Reflect, and ProcessAnalyzer. The framework is based on a collection of use cases. A use case consists of a typical application of process mining functionality in a practical situation. The set of use cases was collected based on the functionality available in ProM and was validated by conducting a series of semi-structured interviews with process mining users and by conducting a survey. The validated collection of use cases formed the base of her tool evaluation. The project was conducted within Fluxicon and was created based on a request from Siemens. The work also resulted in a paper presented at the BPI workshop in Clermont-Ferrand in 2011.

Type

AIS / External / Fluxicon

Links
Staff involved

Stefania Rusu

Discovery and analysis of field service engineer process using process mining

Description

In her thesis, Stefania Rusu applied process mining techniques using event logs from Philips Healthcare to get insights into the workflow of Field Service Engineers. In order to get insights into Philips’s Field Service Engineers Stefania created hierarchical models that abstract from the low levels at which events are stored to higher levels of activities, based on the role of the analyst. Performance analysis based on process mining techniques helped to identify bottlenecks and thereby generated ideas for improvement regarding the work of Field Service Engineers within Philips Healthcare. Stefania proposed a new approach to annotate process maps with performance information extracted from event logs. To support the approach and to apply in in practice, she implemented a new plug-in in the ProM framework.

Type

AIS / External / Philips Healthcare

Links
Staff involved

Erasmus Mundus Joint Master in the field of Big Data Management and Analytics

The department of Computer Science at Technische Universiteit Eindhoven (TU/e) in a consortium of five European Universities is awarded EU co-funding to run a Erasmus Mundus Join Master Degree (EMJMDs) in the field of Big Data Management and Analytics (BDMA).

The programme curriculum is jointly delivered by Université libre de Bruxelles (ULB), Belgium, Universitat Politècnica de Catalunya (UPC), Spain, Technische Universität Berlin (TUB), Germany, Technische Universiteit Eindhoven (TU/e), the Netherlands, and Université François Rabelais Tours (UFRT), France. Academic partners around the world and partners from leading industries in BI and BD, private R&D companies, excellence centres, service companies, start-up incubators, public research institutes, and public authorities will contribute to the programme by giving lectures, training students, providing software, course material, and internships or job placements. The EMJMD in “Big Data Management and Analytics” (BDMA) is designed to provide understanding, knowledge, and skills in the broad scope of fields underlying Business Intelligence (BI) and Big Data (BD). Its main objective is to train computer scientists who have an in-depth understanding of the stakes, challenges, and open issues of gathering and analysing large amounts of heterogeneous data for decision-making purposes. The programme will prepare the graduates to answer the professional challenges of our data-driven society through a strong connection with industry, but also to pursue their studies into doctorate programmes through a strong connection with research and innovation

BDMA is a 2-year (120 ECTS) programme. The first two semesters are devoted to fundamentals on BI and BD delivered by ULB and UPC. Then, all students participate to the European Business Intelligence and Big Data Summer School (eBISS). In the third semester, students chose one of the three specialisations delivered by TUB, TU/e, and UFRT. The fourth semester is dedicated to the master's thesis and can be carried out as an internship in industry or in a research laboratory in any full or associated partner. Eventually, all students attend the Final Event devoted to master's theses defences and the graduation ceremony. The tuition language is English. The program targets students with a Bachelor of Science (or a level equivalent to 180 ETCS) with major in Computer Science, as well as an English proficiency corresponding to level B2 of CEFR. The programme will deliver a joint degree to graduates following the mobility ULB, UPC, and UFRT, and three degrees from ULB, UPC, and the university of the specialisation (UFRT, TUB or TU/e) to graduates following the other mobilities.

More information can be found on the UFRT BDMA site, which will open soon.


If you have a master project item for this page, which may include possible master project assignments, on-going master projects, and completed master projects, please send it to Eric Verbeek.