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Scientific publications
Journal article
Academic publ. refereed

Book chapter
Academic publ. refereed

Academic publications

Proceedings & Conference Contributions
Academic publ. refereed

Reports and Master Theses
Academic publ. non-refereed

Other Products
Journal Papers
Other prod. of scientific act.

Edited Books
Other prod. of scientific act.
dataset (thumb-nail sketch)
Other prod. of scientific act.

Previous years



Research Projects


Behavior Oriented Service Substitution


The Service Oriented Computing (SOC) paradigm aims at building complex systems by composing them from less complex systems, called services. Such a (complex) system is a distributed application often involving several cooperating enterprises. As a system is usually subject to change, individual services will be substituted by other services during the system's life-cycle. Substituting one service by another one should not affect the correctness of the overall system. Verification of correctness is challenging, as the overall system is usually not known to any of the involved enterprises. The focus of the BOSS project is to study service substitution for a set of practical relevant correctness notions. The project is funded by NWO.

Staff involved


Configurable Services for Local Governments


The Software as a Service (SaaS) paradigm is particularly interesting for situations where many organizations need to support similar processes. Since there are 441 municipalities in the Netherlands and they are all providing similar services and are executing similar processes, the use of SaaS technology could potentially be very beneficial for these local governments. Therefore, the aim of the CoSeLoG project is to create a cloud infrastructure for municipalities. Such a cloud would offer services for handling various types of permits, taxes, certificates, and licences.

Although municipalities are similar, their internal processes are typically different. Within the constraints of national laws and regulations, municipalities can differentiate because of differences in size, demographics, problems, and policies. Therefore, the cloud should provide configurable services such that products and processes can be customized while sharing a common infrastructure. The CoSeLoG project aims at the development and analysis of such services. For this we want to use earlier work on configurable process models done at TU/e, QUT, and UT.

One challenge is to actually describe the different variants of a particular municipal service in a single model that can be used to generate the actual configured services. Note that many different variants of a particular service may run in parallel in our cloud. Such a cloud infrastructure for municipalities enables new types of analysis as there is detailed data about the execution of different variants of a given process in different organizations.

A challenge is to develop new process mining techniques that allow for the comparison of event logs of different variants of the same process. Such techniques should highlight differences and commonalities and should assist municipalities in configuring services in a better manner.

The following municipalities are involved in this so-called Jacquard project: Bergeijk, Bladel, Coevorden, Eersel, Emmen, Gemert-Bakel, Hellendoorn, Reusel de Mierden, and Zwolle.

Staff involved


Desire Lines in Big Data


The goal of process mining is to extract process-related information from event logs, e.g., to automatically discover a process model by observing events recorded by some information system. Despite recent advances in process mining there are still important challenges that need to be addressed. In particular with respect to handling large-scale event logs. DeLiBiDa aims to develop new techniques to deal with massive event data. There are various settings where it is impossible to store events over an extended period. Therefore, we want to develop techniques for storing large event logs efficiently, for example in databases. Furthermore, we aim to develop in-database (pre)processing techniques to facilitate existing as well as new to be developed process mining technology. Finally, we plan to develop query techniques to make event-data quickly accessible for processing.

Staff involved


Data Science Center Eindhoven


Recent technological and societal changes led to an explosion of digitally available data. Exploiting the available data to its fullest extent, in order to improve decision making, increase productivity, and deepen our understanding of scientific questions, is one of today's key challenges. Data science is an emerging area that aims to address this challenge. It is a multi-disciplinary area, where computer science and mathematics play crucial roles. The Graduate Program on Data Science leverages the presence at the TU/e of excellent research groups in the data-science area, and to give highly talented students the opportunity to be educated in and contribute to this exciting area. The positions are funded by the NWO Graduate Program.

The Graduate Program on Data Science is part of the Data Science Center Eindhoven (DSC/e), launched in December 2013. It builds on the excellence of several research groups within the department that together cover many of the core topics in data science: algorithms, visualization, data mining, process mining, statistics and probability, stochastics, operations research, and optimization. This ensures a stimulating and excellent environment for the selected students.

The projects fall at the intersection of computer science and mathematics, and are expected to open up promising connections between these fields. Together with the intended supervisors from the relevant research group(s), the students will have the opportunity to define their own research project. The overall aim is to make fundamental advances in the area of Data Science.

Staff involved


European Data Science Academy


The European Data Science Academy (EDSA) will establish a virtuous learning production cycle whereby we: a) analyse the required sector specific skillsets for data analysts across the main industrial sectors in Europe; b) develop modular and adaptable data science curricula to meet these needs; and c) deliver training supported by multi-platform and multilingual learning resources based on our curricula. The curricula and learning resources will be continuously evaluated by pedagogical and data science experts during both development and deployment.

Staff involved


X-ray for Business Processes


Fluxicon is a spin-off of the process mining research done at TU/e. Two STW Valorisation Grants (Phase 1 & 2) have been granted to set up a process mining company that will develop easy-to-use process mining software.

Staff involved

Philips Flagship


The Data Science Centre Eindhoven (DSC/e) is TU/e’s response to the growing volume and importance of data and the need for data & process scientists ( The DSC/e has recently started a long-term strategic cooperation with Philips Research Eindhoven on three topics: data science, health and lighting. As a first concrete action, 70 PhD students are being hired for these three topics using joint funding from the TU/e and Philips, of which 18 PhD students work on the data science topic. These students form together with researchers from the TU/e and Philips a strong research community working together on scientific and industrial challenges.

The following four PhD positions will be related to the topic of process mining:

  1. Product-centric Consumer Data Analytics: Product Usage Lifecycle Analysis [part of the “Data Driven Value Proposition” theme] Digital components are being added to Philips lifestyle products. The data from these products as well as from Philips touch points must be combined to optimize user experience and maintain customer satisfaction. Process mining techniques will be used to analyze the usage of products over a longer period of time.
  2. Transforming Event Data into Predictive Models [part of the Healthcare Smart Maintenance theme] Philips has strong leadership positions in healthcare imaging and patient monitoring systems. In the healthcare domain, reducing equipment downtime and cost of ownership for hospitals is of vital importance. Smart maintenance exploits that professional equipment is connected to the internet and aims to use event and sensor data for overall cost reduction. Process mining techniques will be used to learn dynamic models that can be used for prediction and optimization.
  3. Predictive Analytics for Healthcare Workflows
  4. Radiology Workflow Optimization and Orchestration [both part of the Optimizing Healthcare Workflows theme] The delivery of patient care in hospital is a complex workflow based on fixed protocols.

Optimization of patient care at reduced cost requires the orchestration of multiple clinical workflows. Timely getting the imaging/lab tests done and getting the results back to physicians can help quickly diagnose/treat the patient, and save lives. The rapid digitization of diagnostics in radiology and pathology calls for a data-driven optimization of the workflows. Process mining will be used to learn models for the as-is situation. However, process technology will also be used to improve the processes.

Staff involved


“Propelling Business Process Management by Research and Innovation Staff Exchange”


RISE_BPM is the first favourably evaluated project proposal submitted by the University of Münster in cooperation with ERCIS partners within the Horizon 2020 EU funding programme. The RISE_BPM project is aimed at networking world-leading research institutions and corporate innovators to develop new horizons for Business Process Management (BPM). The project consortium, besides the University of Münster as the coordinator, includes partners from Australia, South Korea, Brazil, Austria, Spain, the Netherlands, and Liechtenstein.

RISE_BPM was set up to ensure the sustainability and further extension of the collaboration ties established during the Networked Service Society (NSS) project. NSS (Project number: APR 10/805) is a multi-national project funded by the International Bureau of the German Federal Ministry of Education and Research (BMBF). The project was conducted from July 2010 until the end of 2014 and was aimed at establishing and strengthening long-term collaboration structures with institutions in the Asian-Pacific region in the areas of Joint Research, Joint Education and Joint Industry Projects.

RISE_BPM will last for four years and started May 1st 2015.

Staff involved

If you have a project item for this page, please send it to Eric Verbeek.


The Berlin - Eindhoven - Rostock Service Technology Program (B·E·S·T)

It is increasingly understood that services provide the right level of abstraction for the emerging paradigm of Programming-in-the-Large or Programming-in-the-world. Service-oriented architectures are about to revolutionize software architectures as fundamental as the event of Object-Orientation did 25 years ago.

Working groups centered at Humboldt-Universität zu Berlin, at Eindhoven Technical University and at Universität Rostock bundle their ongoing efforts in the area of Service Technology, aiming at strengthening their impact on research and application.

Visit the B·E·S·T site.


The Business Process Management (BPM) group at the Queensland University of Technology (QUT)

The BPM group at QUT, is one of the fastest growing BPM research groups in the world with impressive academic achievements, significant third-party funded research projects and major industry linkages.

Visit the BPM / QUT site.


The Department of Computer Science at the Universitat Politècnica de Catalunya

The Computer Science department (CS) of the Technical University of Catalonia (UPC) teaches and research in areas related to algorithmics, computer graphics, artificial intelligence, logic and programming.

Visit the CS / UPC site.

CS / UniBZ

The Faculty of Computer Science (CS) at the Free University of Bozen - Bolzano (UniBZ)

Seamless integration of teaching, research and application.

An innovative, integrated approach forms the core framework of the teaching, research and practical applications of the Faculty.

Visit the CS / UniBZ site.


The Data Science Center Eindhoven (DSC/e)

The Data Science Center Eindhoven (DSC/e) is TU/e’s response to the growing volume and importance of data. 90% of the data in the world today has been created in the last two years alone and the world's data will grow by 50 times in the next 10 years. Moreover, human and organizational activities are intertwined with the digital universe. Therefore, data science is growing in importance and becoming an integral part of different types of engineering and scientific research.

Visit the DSC/e site.

IS / IE&IS / TU/e

The Information Systems group (IS) at the School of Industrial Engineering (IE&IS) at the Eindhoven University of Technology (TU/e)

The mission of the IS Group is to research and teach design, analysis, and use of advanced information systems for (re)design and support of operational business processes, both within the boundaries of a single organization and across these boundaries in the context of business service networks and industrial supply chains,

  • aiming at a balance between theoretical foundation and practical application,
  • harmonizing the demand pull and technology push developments in the field, and
  • taking process modeling, architecture design and software management as focal areas.

Visit the IS / IE&IS / TU/e site.

IS / M&CS / TU/e

The Information Systems group (IS) at the Department of Mathematics and Computer Science (M&CS) at the Eindhoven University of Technology (TU/e)

The section Information Systems (IS) occupies itself with designing and building software systems for storage and distribution of information.

Visit the IS / M&CS / TU/e site.

M&CS / Weizmann

The Faculty of Mathematics and Computer Science (M&CS) at the Weizmann Institute of Science

Visit the M&CS / Weizmann site.


The Laboratory of Process-Aware Information Systems (PAIS Lab) at HSE Moscow

The PAIS lab was founded in January 2013. It is a division of HSE Faculty of Computer Science. We conduct research on process-aware information systems and process mining. Good examples of PAISs are BPM systems, Workflow Management systems, ERP systems, and case handling systems. Our main goal is to develop new methods and approaches in modelling, analysis, and design of such systems.

Visit the PAIS / HSE site.

SEG / CS / Tartu

The Software Engineering Group (SEG) at the Institute of Computer Science (CS) at the University of Tartu

The Software Engineering Group at University of Tartu's Institute of Computer Science conducts research and teaching in the field of software engineering with an emphasis on business process management and software process improvement.

In addition to implementing national and European research projects, the group is engaged in the Software Technology and Applications Competence Center - an industry-driven R&D that aims to develop next-generation solutions in the fields of data mining and software services.

Visit the SEG / CS / Tartu site.


The Netherlands Research School for Information and Knowledge Systems (SIKS)

The School for Information and Knowledge Systems (SIKS) is a Dutch Research School established in 1996 and accredited by the Royal Netherlands Academy of Arts and Sciences. SIKS is a network institute in which over 450 research fellows and Ph.D. students from 11 different universities collaborate.

Visit the SIKS site.

SOS / Tsinghua

The School Of Software (SOS) at Tsinghua University

Visit the SOS / Tsinghua site.

If you have an update for this page, please send it to Eric Verbeek.




Process Mining


The Process Mining Framework in which all our process-mining related ideas are implemented. If you want to see our research at work, download the latest release of ProM.


CPN Tools

Coloured Petri Net Tools


CPN Tools is a tool for editing, simulating, and analyzing Colored Petri nets. The tool features incremental syntax checking and code generation, which take place while a net is being constructed. A fast simulator efficiently handles untimed and timed nets. Full and partial state spaces can be generated and analyzed, and a standard state space report contains information, such as boundedness properties and liveness properties.



Yet Another Workflow Language


YAWL is a BPM/Workflow system, based on a concise and powerful modelling language, that handles complex data transformations, and full integration with organizational resources and external Web Services. YAWL offers:

  • the most powerful process specification language for capturing control-flow dependencies and resourcing requirements.
  • native data handling using XML Schema, XPath and XQuery.
  • a formal foundation that makes its specifications unambiguous and allows automated verification.
  • a service-oriented architecture that provides an environment that can easily be tuned to specific needs.
YAWL Server

We have a running YAWL server (, which is being maintained by QUT. Please ask Eric Verbeek for details if you want to use this server.

  • YAWL (includes downloads)



Executable Specification tool.


Workflow Analyzer (Now part of ProM).


Yet Another Smart Process EditoR.



Aalst, Wil van der HGL MF 7.103 4295 Home Scholar Employee
Bolt Iriondo, Alfredo PhD Stud. MF 7.108 8649 Home Employee
Buijs, Joos PD MF 7.062 3661 Home Scholar Employee
de Leoni, Massimiliano UD MF 7.059 8430 Home Scholar Employee
Dixit, Alok n.a. MF 7.122 - Employee
Dongen, Boudewijn van UD MF 7.064 2181 Home Scholar Employee
Dornostup, Yulia OWP MF 7.106 - Employee
Eck, Maikel van PhD Stud. MF 7.108 8707 Employee
Fahland, Dirk UD MF 7.066 4804 Home Scholar Employee
Firat, Murat PD MF 7.106 8710 Home Employee
González Lopéz de Murillas, Eduardo PhD Stud. MF 7.117 8648 Home Scholar Employee
Hee, Kees van HGL em MF 7.122 4518 Scholar Employee
Heidari, Farideh UD MF 7.119 2257 Home Scholar Employee
Hompes, Bart PhD Stud. MF 7.060 8941 Home Scholar Employee
Koorneef, Marie PhD Stud. MF 7.109 7393 Employee
Korolev, Dmitry OWP MF 7.117 8523 Employee
Leemans, Maikel PhD Stud. MF 7.117 4831 Scholar Employee
Leemans, Sander PhD Stud. MF 7.106 8345 Scholar Employee
Li, Guangming PhD Stud. MF 7.109 2584 Employee
Ligt, Ine van der Secretary MF 7.101 2087 Employee
Liu, Cong Phd Stud. MF 7.106 2087 Scholar Employee
Lu, Xixi PhD Stud. MF 7.060 8468 Home Scholar Employee
Mannhardt, Felix PhD Stud. MF 7.117 3425 Scholar Employee
Mukala, Patrick OWP MF 7.108 8522 Employee
Nuijten, Wim HGL MF 7.117 3877 (2733) Employee
Ramezani, Elham PhD Stud. MF 7.109 4593 Scholar Employee
Reijers, Hajo HGL MF 7.122 3629 Home Scholar Employee
Schunselaar, Dennis PhD Stud. MF 7.109 5674 Home Scholar Employee
Sidorova, Natalia UD MF 7.105 3705 Home Scholar Employee
Tax, Niek PhD Stud. MF 7.108 8965 Home Scholar Employee
Verbeek, Eric OBP MF 7.062 3755 Home Scholar Employee
Zelst, Bas van PhD Stud. MF 7.060 8687 Home Scholar Employee

Office Map




Postdoc candidate in the Desire Lines in Big Data project

View this vacancy online and apply directly: In the context of the NWO project “Desire Lines in Big Data” we are looking for a Postdoc interested in Process Mining on huge, heterogeneous event logs.

The DeLiBiDa project as a whole runs for a period of four years and aims to develop new process mining technology to analyse big event logs. It is supported by the Dutch Organisation for Scientific Research (NWO).

→

PhD candidate in the Desire Lines in Big Data project

View this vacancy online and apply directly:

In the context of the NWO project “Desire Lines in Big Data” we are looking for a PhD candidate interested in Process Mining on huge, heterogeneous event logs.

The DeLiBiDa project as a whole runs for a period of four years and aims to develop new process mining technology to analyse big event logs. It is supported by the Dutch Organisation for Scientific Research (NWO).

→

Several PostDoc positions in Process Mining/Data Science

Data science, and process mining in particular, is growing in importance. Therefore, we have several postdoc vacancies for people with a strong background in data mining, machine learning, process analytics, predictive analytics, or Big Data. Currently, we are looking for:

PostDocs working on Process Mining/Data Science

The AIS group is one of the leading groups in the exciting new field of process mining ( Process mining techniques focus on process discovery (extracting process models from event logs), conformance checking (comparing normative models with the reality recorded in event logs), and extension (extending models based on event logs). The work resulted in the development of the ProM framework that is widely used in industry and serves as a platform for new process mining techniques used by research groups all over the globe. Moreover, many of the techniques developed in the context of ProM have been embedded in commercial tools. See also

The Data Science Centre Eindhoven (DSC/e) is TU/e’s response to the growing volume and importance of data ( For example, in TU/e's Impulse program we collaborate with innovative organizations such as Perceptive Software and Philips on topics related to data science and process mining.

In the context of various research projects we are looking for several PostDocs working on process mining and related topics:

  • We are looking for a PostDoc working on Big Data and process mining. Events are growing and detailed analysis based on formal and precise models is often infeasible without distribution or innovative mining approaches.
  • We are looking for a PostDoc working on process mining and software analytics in the context of the 3TU.BSR project.
  • New projects and topics might be added in the near future.

→

Older entries >>

If you have a vacancy item for this page, please send it to Eric Verbeek.