• De Zaale, Atlas 5.402

    Eindhoven

    Netherlands

  • P.O. Box 513, Atlas

    5600 MB Eindhoven

    Netherlands

Organization profile

Introduction / mission

The Information Systems (IS) group studies design, optimization and computer-aided decision support in operational processes within and between organizations.

Highlighted phrase

Create value through intelligent processing of business information

Organisational profile

The Information Systems (IS) Group at Eindhoven University of Technology (TU/e) operates within the general area of business information systems. Our research focuses on the design, optimization and computer-aided support of operational processes within and between organizations through business process engineering. We study implications for information systems, information system design, governance and decision support. The research focus includes design methods, analysis tools, information system architectures, data mining and intelligent systems development using advanced prototypes. Our approach is model-centric and engineering-oriented, integrating basic and applied research with contemporary real-world cases.

Business organizations increasingly depend on their information systems to align internalorganization structures and deal with the complexity and changeability of markets. Up-to-date, complete and accurate information from big data has become a necessity to survive in an increasingly competitive world. As overseeing operations becomes too complicated for humans, business requirements related to information systems are growing exponentially. Rapid developments in information technology enable application types unimaginable a few years ago. Information systems are vital for the design and control of successful operational processes. Increasing complexity and dependence on information systems are driving  significant changes across many sectors, from logistics, mobility services and hi-tech manufacturing to healthcare. 

IS research concentrates on the following: 

  • Process modeling, architecture design and software management
  • Optimal decision support and intelligent system design
  • Balancing theoretical foundation and practical application 
  • Harmonizing demand-pull and technology-push developments in the field  
  • Business Process Engineering for Smart Mobility and HealthCare

The IS group studies implications for information system architectures and design, business process modeling, governance and decision support and distinguishes three research clusters: Business Engineering, Process Engineering and Business Intelligence. Application areas include hightech industry, logistics, mobility, healthcare, and services.

Business Engineering (BE) focuses on the investigation and development of new concepts, methods, and techniques for the development and implementation of innovative business solutions. This involves the support for the engineering of business models into business processes, organizational structures, architectures, and information systems, and connecting all aspects of digital transformation. It emphasizes on customer/user orientation and focuses not only on the technical design of new business solutions, but also on their strategic, governance, human and cultural dimensions.

Process Engineering (PE) is devoted to the investigation and development of new concepts, models, techniques, tools and application scenarios for the analysis and (re)design of operational business processes. Topic areas include data-driven engineering of business processes, human aspects of process engineering, decision support for business processes, process mining, mapping business models to business processes, mapping business processes onto system architectures.

Business Intelligence (BI) develops methods, techniques and tools for advanced analysis of business processes and optimal decision-making in their execution. Data mining, text mining, process mining, machine learning and computational intelligence methods are applied for building consistent models that make use of different modalities of data from multiple sources. These approaches can be used to design and improve information system for developing intelligent decision support with which organizations can fulfil their goals of operational excellence and improved decision making.

More information

Fingerprint Dive into the research topics where Information Systems IE&IS is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

  • Network Recent external collaboration on country level. Dive into details by clicking on the dots.

    Projects

    Research Output

  • A latitudinal study on the use of sequential and concurrency patterns in deviance mining

    Genga, L., Potena, D., Chiorrini, A., Diamantini, C. & Zannone, N., 1 Jan 2020, Studies in Computational Intelligence. Appice, A., Ceci, M., Loglisci, C., Manco, G., Masciari, E. & Ras, Z. (eds.). Cham: Springer, p. 103-119 17 p. (Studies in Computational Intelligence; vol. 880).

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

  • 1 Downloads (Pure)

    A method for operationalizing service-dominant business models

    Suratno, B., 17 Mar 2020, Eindhoven: Technische Universiteit Eindhoven. 179 p.

    Research output: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)

    Open Access
    File

    Datasets

    Prizes

    2nd prize in The Executable Paper Grand Challenge

    Pieter Van Gorp (Recipient), 2011

    Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific

    Best Demo Award

    Remco M. Dijkman (Recipient), 2019

    Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific

  • Best Industrial Paper Award

    Herbert van Leeuwen (Recipient), Yingqian Zhang (Recipient), Kalliopi Zervanou (Recipient), Shantanu Mullick (Recipient), Uzay Kaymak (Recipient) & Tom de Ruijter (Recipient), 2020

    Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific

    Activities

    34rd AAAI Conference on Artificial Intelligence

    Yingqian Zhang (Member of programme committee)
    2020

    Activity: Participating in or organising an event typesConferenceScientific

    Data Science Meets Optimisation

    Yingqian Zhang (Organiser)
    2020

    Activity: Participating in or organising an event typesWorkshop, seminar, course or exhibitionScientific

    Improving ambulance dispatch policy using AI

    Yingqian Zhang (Invited speaker)
    6 Nov 2019

    Activity: Talk or presentation typesInvited talkScientific

    Student theses

    Accurate response to fluctuating demand with regard to promotions in the online retailing industry

    Author: Kiemeneij, N., 31 Jan 2018

    Supervisor: Atan, Z. (Supervisor 1), Mutlu, N. (Supervisor 2) & Firat, M. (Supervisor 2)

    Student thesis: Master

    File

    Achieving more accurate truck warning lights by descriptive and predictive analytics

    Author: van de Donk, W., 31 May 2019

    Supervisor: Zhang, Y. (Supervisor 1), Kaymak, U. (Supervisor 2) & Zervanou, K. (Supervisor 2)

    Student thesis: Master

    File

    A clinical decision support system by using wrist-worn smartphone tremor measurements: at the Maastricht University Medical Center

    Author: Zamora, G., 30 Jun 2017

    Supervisor: Kaymak, U. (Supervisor 1), Wilbik, A. (Supervisor 2) & Van Gorp, P. (Supervisor 2)

    Student thesis: Master

    File