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Research

Publications

2016

Article
Scientific peer reviewed

2015

Article
Scientific peer reviewed

Scientific not peer reviewed

Chapter
Scientific peer reviewed

Scientific not peer reviewed

Conference Contribution
Scientific peer reviewed

Book
Scientific

Report
Scientific

Previous years

Miscellaneous

Projects

Research Projects

3TU.BSR

3TU - Big Software on the Run

Description

Millions of lines of code - written in different languages by different people at different times, and operating on a variety of platforms - drive the systems performing key processes in our society. The resulting software needs to evolve and can no longer be controlled a priori as is illustrated by a range of software problems. The 3TU.BSR research program will develop novel techniques and tools to analyze software systems in vivo - making it possible to visualize behavior, create models, check conformance, predict problems, and recommend corrective actions.

Staff involved

BOSS

Behavior Oriented Service Substitution

Description

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

Core

CORE - Consistently Optimised REsilient secure global supply-chains

Description

The CORE project aims to produce cost effective, fast and robust solutions for worldwide Global Supply Chain system. The project will implement an ecosystem where interoperability, security, resilience and real-time are optimized. The role of the AIS group in the project is to employ process mining and determine security risks and other supply chain threats and their impact on supply chain flows around the world. The project will demonstrate the tangible benefits to involved stakeholders (transaction, transport, regulatory and financial operators), thus facilitating its adoption by commercial entities.

Links
Staff involved

CoSeLoG

Configurable Services for Local Governments

Description

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.

Links
Staff involved

DAIPEX

DAIPEX - Data and Algorithms for Integrated transport Planning and EXecution

Description

Transport companies often discover that what takes place in day-to-day transportation is not in line with their transport plans. This is largely due to the fact that the software which is employed in creating transport plans, fails to account for the real-world complexity of transportation and logistics. Approximations and abstractions used fall short of the true complexities in the real world. Direct consequences include violation of time windows, unnecessary delays, underutilized transportation capacity, etc.

This project aims to develop algorithms and software that can handle time-dependent, stochastic, planning problems, employing high-volumes of information. We will focus particularly on the complexities that arise in integrating planning problems and stochastic dependencies in Cross Chain Control Centers (4C), because in a 4C: i) the required real-life detail increases, ii) incidents are considerably larger, and iii) more communication is required as the pressure on response time increases.

Links
Staff involved

DeLiBiDa

Desire Lines in Big Data

Description

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.

Links
Staff involved

DSC/e & NWO Graduate Program

Data Science Center Eindhoven

Description

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.

Links
Staff involved

EDSA

European Data Science Academy

Description

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.

Links
Staff involved

Fluxicon

X-ray for Business Processes

Description

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.

Links
Staff involved

Philips Flagship

Description

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 (http://www.tue.nl/dsce/). 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 [part of the Optimizing Healthcare Workflows theme]. Processes play an important role in pathology and radiology. It is not just about collecting data and supporting individual activities, but also about improving the underlying end-to-end workflow processes. To improve these operational processes in terms of costs, efficiency, speed, reliability, and conformance, we can learn from the way that processes are conducted in practice. One can learn from problems in the past and compare different process variants and process instances. This project aims to obtain insight in these workflows, in order to understand what goes well and what can be improved, using a process mining approach. The cross-fertilization between process mining and visualization will provide a novel angle on workflow improvements in pathology and radiology.
  4. Radiology Workflow Optimization and Orchestration [also part of the Optimizing Healthcare Workflows theme]. Radiology, involves complex workflows, especially when seen in its clinical context. This project aims to obtain insight in these workflows and their visualization, in order to understand what goes well and what can be improved, using a visual analytics approach, where automated processing and interactive exploration are tightly integrated.

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.

Links
Staff involved

Process Mining in Logistics

Process Mining in Logistics is a joint project of the Data Science Center Eindhoven and Vanderlande industries.

Description

Logistics processes are notoriously difficult to design, analyze, and to improve. Where classical processes are scoped around the processing of information associated to a specific unique case, logistics deals with physical objects that are grouped and processed together with other physical objects in one process at one or more physical locations, then distributed and later on re-aggregated with other physical objects in another process at other physical locations. In essence, logistics deals with numerous processes, cases, and objects that interact with each other in a multi-dimensional fashion. On one hand, this subjects logistics processes to many external influences which can have a negative impact on process outcomes and process performance. On the other hand, when analyzing the performance of flows across networks of logistics, the multi-dimensional nature is especially prevalent and existing data-driven process analysis techniques such as process mining which assume a single viewpoint cannot be applied.

Vanderlande is the global market leader in baggage handling systems for airports and sorting systems for parcel and postal services, and also a leading supplier of warehouse automation solutions. The company recognizes the emerging trend of more data driven business models and addressed ‘big data’ a key topic on the technology roadmap. Therefore, under the umbrella of the Data Science Impuls program, the DSC/e and Vanderlande joined forces in a research project.

The project runs from September 2016 until August 2020.

Project Objectives

The goal of the joint research project of DSC/e and Vanderlande is to lift process mining to the multi-dimensional space of logistics, and to allow analyzing logistics processes and systems from all relevant angles and viewpoints. By having thorough and fast insight into logistics and business processes, improvements can be found, predicted, and implemented at Vanderlande delivered logistics solutions. We aim to achieve this lift for the entire process mining spectrum

  • from appropriate data logging and event data extraction techniques from logistics systems
  • and appropriate conceptual modeling of logistics processes and systems
  • via process discovery and process replay techniques for multi-dimensional event data
  • for online and offline deviation detection and process comparison,
  • to predictions of process outcomes and online recommendations based on event data.
Staff Involved

RISE BPM

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

Description

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.

Links
Staff involved

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

B·E·S·T

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.

BPM / QUT

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.

CS / UPC

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.

DSC/e

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.

PAIS / HSE

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.

SIKS

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.

Tools

Tools

ProM

Process Mining

Description

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.

On October 9, 2015, ProM had been downloaded more than 110,000 times in total, of which 27,000 times in the last 12 months.

Links

CPN Tools

Coloured Petri Net Tools

Description

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.

On October 9, 2015, CPN Tools had been downloaded more than 78,000 times in total, of which 10,000 times in the last 12 months.

Links

YAWL

Yet Another Workflow Language

Description

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.

On October 9, 2015, YAWL had been downloaded more than 210,000 times in total, of which 30,000 times in the last 12 months.

YAWL Server

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

Links
  • YAWL (includes downloads)

Discontinued

ExSpect

Executable Specification tool.

Woflan

Workflow Analyzer (Now part of ProM).

YASPER

Yet Another Smart Process EditoR.

Staff

Staff

Current Members

A B C D E F G H K L M N R S T V Z

A
Wil van der Aalst
Position: HGL
Room: MF 7.103
Tel (internal): 4295
Projects: 3TU.BSR, Core, CoseLog, DeLiBiDa, DSC/e & NWO Graduate Program, Fluxicon, Phlips Flagship, Process Mining in Logistics, RISE BPM
Courses: 2IIE0, 2IMI05, 2IMI20, 2IMI35
Links: Personal home page, Google scholar page, TU/e employee page, DSC/e
Prof.dr.ir. Wil van der Aalst is a full professor of Information Systems and chair of the AIS group. He is also the scientific director of the Data Science Center Eindhoven (DSC/e). His personal research interests include process mining, business process management, workflow management, Petri nets, process modeling, and process analysis.
Nour Assy
Position: PD
Room: MF 7.117
Tel (internal): 8649
Projects: 3TU.BSR
Courses:
Links: Google scholar page, TU/e employee page
B
Hilda Fabiola Bernard
Position: PhD Student
Room: MF 7.109
Tel (internal):
Projects: Process Mining in Logistics
Courses:
Links:
Alfredo Bolt Iriondo
Position: PhD Student
Room: MF 7.108
Tel (internal): 8649
Projects:
Courses:
Links: Personal home page, TU/e employee page
Rémi Brochenin
Position: PD
Room: MF 7.108
Tel (internal): 3487
Projects: EDSA
Courses:
Links: Personal home page, TU/e employee page
Joos Buijs
Position: UD
Room: MF 7.062
Tel (internal): 3661
Projects: CoseLog, EDSA, Phlips Flagship, RISE BPM
Courses: 2IMI20
Links: Personal home page, Google scholar 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!
C
Long Cheng
Position: PD
Room: MF 7.109
Tel (internal): 3635
Projects:* DeLiBiDa
Courses:
Links: Personal home page, TU/e employee page
D
Massimiliano de Leoni
Position: UD
Room: MF 7.059
Tel (internal): 8430
Projects: Core
Courses: 2IHI10/2IIC0, 2IIE0, 2IMI35
Links: Personal home page, Google scholar page, TU/e employee page
Vadim Denisov
Position: PhD Student
Room: MF 7.109
Tel (internal):
Projects: Process Mining in Logistics
Courses:
Links:
Alok Dixit
Position: PhD Student
Room: MF 7.122
Tel (internal): -
Projects: Phlips Flagship
Courses:
Links: Google scholar page, TU/e employee page
Boudewijn van Dongen
Position: UD
Room: MF 7.064
Tel (internal): 2181
Projects: 3TU.BSR, CoseLog, DeLiBiDa
Courses: 2IMC92, 2IMC97, 2IMI30
Links: Google scholar 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.
E
Maikel van Eck
Position: PhD Student
Room: MF 7.108
Tel (internal): 8707
Projects: RISE BPM
Courses:
Links: Google scholar page, TU/e employee page
Maikel is a PhD student within the AIS group where his main research is in the area of process mining. More concretely, his research focuses on the use of process mining techniques to investigate the relations between the behavior of people and their health. Applications of this are found in the area of work-related stress management. Other research interests include event aggregation, pattern prediction and process mining case studies.
F
Dirk Fahland
Position: UD
Room: MF 7.066
Tel (internal): 4804
Projects: BOSS, Process Mining in Logistics
Courses: 2IHI10/2IIC0, 2IMI10, 2IOC0, JBG030
Links: Personal home page, Google scholar 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.
Murat Firat
Position: PD
Room: MF 7.106
Tel (internal): 8710
Project: DAIPEX
Courses:
Links: Personal home page, TU/e employee page
Murat Firat obtained his PhD degree from Mathematics and Computer Science Dept. of Eindhoven University of Technology. After completing his PhD study, he worked at France Telecom a post-doctoral researcher. His research interests are in several applications in combinatorial optimization like multi-skill workforce scheduling, Gale-Shapley stability in assignments, design of fiber optic networks and vehicle routing problems.
G
Eduardo González Lopéz de Murillas
Position: PhD Student
Room: MF 7.117
Tel (internal): 8648
Projects:
Courses:
Links: Personal home page, Google scholar page, TU/e employee page
H
Marwan Hassani
Position: UD
Room: MF 7.097A
Tel (internal): 3887
Projects:
Courses: 2IHI10/2IIC0
Links: Personal home page, Google scholar page, TU/e employee page
Kees van Hee
Position: HGL em
Room: MF 7.122
Tel (internal): 4518
Projects:
Courses:
Links: Google scholar page, TU/e employee page
Farideh Heidari
Position: UD
Room: MF 7.119
Tel (internal): 2257
Projects:
Courses: 2IMC93, 2IMC98
Links: Personal home page, Google scholar 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.
Bart Hompes
Position: PhD Student
Room: MF 7.060
Tel (internal): 8941
Projects: Phlips Flagship, RISE BPM
Courses:
Links: Personal home page, Google scholar page, TU/e employee page
Bart is an enthusiastic, fast-learning team-player eager to learn and develop new technologies. Bart's broad interests lie in the fields where business meets technology, such as BPM, BI and BIS. Bart likes to work in international, research-oriented environments with relations to practical applications and implementation. In his spare time Bart likes to ride my motorcycle and play motoball.
K
Marie Koorneef
Position: PhD Student
Room: MF 7.109
Tel (internal): 7393
Projects: Phlips Flagship
Courses:
Links: TU/e employee page
L
Maikel Leemans
Position: PhD Student
Room: MF 7.117
Tel (internal): 4831
Projects: 3TU.BSR, DSC/e & NWO Graduate Program, RISE BPM
Courses:
Links: Personal home page, Google scholar page, TU/e employee page
Maikel is a PhD student within the AIS group where his main research is in the area of process mining. More concretely, his research interests focus on the analysis of software, where he looks at finding common usage patterns, possible deviations and options how to improve the usage process by changing the software.
Sander Leemans
Position: PhD Student
Room: MF 7.106
Tel (internal): 8345
Projects: ABAPM (Avoid Blind Alleys in Process Mining)
Courses:
Links: Google scholar page, TU/e employee page
Guangming Li
Position: PhD Student
Room: MF 7.109
Tel (internal): 2584
Projects:
Courses:
Links: Personal home page, TU/e employee page
Ine van der Ligt
Position: Secretary
Room: MF 7.101
Tel (internal): 2733
Projects:
Courses:
Links: TU/e employee page
Cong Liu
Position: PhD Student
Room: MF 7.106
Tel (internal): 2087
Projects: 3TU.BSR
Courses:
Links: Google scholar page, TU/e employee page
Xixi Lu
Position: PhD Student
Room: MF 7.060
Tel (internal): 8468
Projects: Price, RISE BPM
Courses:
Links: Personal home page, Google scholar page, TU/e employee page
Xixi is a PhD student within the AIS group where her main research is in the area of process mining. More concretely, her research interests include conformance checking, partial orders and trace clustering.
M
Felix Mannhardt
Position: PhD Student
Room: MF 7.117
Tel (internal): 3425
Projects:
Courses:
Links: Google scholar page, TU/e employee page
Felix received a MSc in Computer Science in 2013 and a BSc in Business Information Systems in 2010, both from Bonn-Rhein-Sieg University of Applied Sciences.
N
Wim Nuijten
Position: HGL
Room: MF 7.122
Tel (internal): 3877 (2733)
Projects: DAIPEX
Courses: 2IMI25
Links: TU/e employee page
R
Elham Ramezani
Position: PhD Student
Room: MF 7.109
Tel (internal): 4593
Projects: BOSS
Courses:
Links: Personal home page, Google scholar page, TU/e employee page
Hajo Reijers
Position: HGL
Room: MF 7.122
Tel (internal): 3629
Projects: CoseLog
Courses: 2IMI00
Links: Personal home page, Google scholar 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.
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Natalia Sidorova
Position: UD
Room: MF 7.105
Tel (internal): 3705
Projects: Phlips Flagship
Courses: 2IIE0, 2IMI15, 2IMI35
Links: Personal home page, Google scholar page, TU/e employee page
Alifah Syamsiyah
Position: PhD Student
Room: MF 7.106
Tel (internal): 2767
Projects: DeLiBiDa
Courses: 2IHI10/2IIC0
Links: Google scholar page, TU/e employee page
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Niek Tax
Position: PhD Student
Room: MF 7.108
Tel (internal): 8965
Projects: Phlips Flagship, RISE BPM
Courses:
Links: Personal home page, Google scholar page, TU/e employee page
Niek is a PhD student within the AIS group where his main research is in the area of process mining. More concretely, his research interests include seasonality detection, deviation detection, predictions and recommendations based on process mining techniques.
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Eric Verbeek
Position: Scientific Programmer
Room: MF 7.062
Tel (internal): 3755
Projects: CoseLog
Courses:
Links: Personal home page, Google scholar page, TU/e employee page
Eric is the scientific programmer in the AIS group. As such, he is the custodian of the process mining framework ProM. In you want access to the ProM repository, or have any questions related to ProM and its development, as Eric. Recently, he has been working on a decomposition framework for both process discovery as conformance checking in ProM. Earlier, he also worked on ExSpect and Woflan.
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Sebastiaan (Bas) van Zelst
Position: PhD Student
Room: MF 7.060
Tel (internal): 8687
Projects: DeLiBiDa, RISE BPM
Courses:
Links: Personal home page, Google scholar page, TU/e employee page
Bas is a PhD student within the AIS group where his main research is in the area of process mining. More concretely, his research interests focus on analysing event streams without storing (too much) data.

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Vacancies

Vacancies

PhD position BrandLoyalty Mining Customer Behavior (V32.2642)

In the context of the joint research programs under the umbrella of JADS, Data Science Center Eindhoven (DSC/e) among BrandLoyalty, we are looking for one PhD student interested in “Mining Customer Behavior to Increase the Effectiveness of Loyalty Programs and Promotions (MiCuB)”.

Position PhD-student
Departments Department of Mathematics & Computer Science
Institutes Data Science Center Eindhoven
FTE 1,0
Date off 31/07/2016
Reference number V32.2642

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Assistant Professor in business process intelligence (V32.2519)

Position Assistant Professor
Departments Department of Mathematics & Computer Science
Institutes Data Science Center Eindhoven
FTE 1,0
Date off 24/04/2016
Reference number V32.2519

Apply now

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Assistant Professor in process mining (V32.2536)

Position Assistant Professor
Departments Department of Mathematics & Computer Science
Institutes Data Science Center Eindhoven
FTE 1,0
Date off 24/04/2016
Reference number V32.2536

Apply now

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