Organization profile

Introduction / mission

The research

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. Our main mission is to bridge the gap between process science (BPM, WFM, formal methods, etc.) and data science. This explain the focus on process mining.

Organisational profile

The research concentrates on formalisms for modeling and methods to discover and analyze models. 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.

The AIS group tries to make research results accessible by providing (open-source) software. 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. Our prototyping framework ProM (process mining and process analysis) illustrates that the problems of tomorrow’s practice are the driving force behind the development of new theory, methods, and tools by AIS.

Master's projects

Many master projects are linked to some external organization. Examples are IBM, Pallas Athena, SAP, ING, Deloitte, AMC Hospital, Justice Department, ASML, Philips Medical Systems, Océ, etc.

See the website for more information on the group and its projects.

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

Petri nets Engineering & Materials Science
Industry Engineering & Materials Science
Information systems Engineering & Materials Science
Semantics Engineering & Materials Science
Flow control Engineering & Materials Science
Specifications Engineering & Materials Science
Web services Engineering & Materials Science
Semantic Web Engineering & Materials Science

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

Projects 2016 2018

Interoperability of Heterogeneous IoT Platforms

Liotta, A., Exarchakos, G., van Hout, J., Mocanu, D., Moerenhout, M., Moerenhout, M., van der Lee, T., van Mil, J. & van Mil, J.


Project: Research direct

Research Output 1974 2019

Adversarial balancing-based representation learning for causal effect inference with observational data

Du, X., Sun, L., Duivesteijn, W., Nikolaev, A. & Pechenizkiy, M., 30 Apr 2019, In : arXiv. 17 p., 1904.13335v1

Research output: Contribution to journalArticleAcademic

Open Access
Deep learning

Evolving and understanding sparse deep neural networks using cosine similarity

Pieterse, J. & Mocanu, D., 17 Mar 2019, In : arXiv. 14 p., 1903.07138v1

Research output: Contribution to journalArticleAcademic

Open Access
Neural networks
Computational complexity

Evolving plasticity for autonomous learning under changing environmental conditions

Yaman, A., Mocanu, D., Iacca, G., Coler, M., Fletcher, G. & Pechenizkiy, M., 2019, In : arXiv. 26 p., 1904.01709v1

Research output: Contribution to journalArticleAcademic

Open Access
Chemical activation
Genetic algorithms

Student theses

Application-grounded evaluation of predictive model explanation methods

Author: Lin, C., 24 Sep 2018

Supervisor: Pechenizkiy, M. (Supervisor 1), van der Zon, S. (Supervisor 2), van Ipenburg, W. (External person) (External coach), Veldsink, J. W. (External person) (External coach) & Papapetrou, O. (Supervisor 2)

Student thesis: Master


Block-sparse evolutionary training using weight momentum evolution: training methods for hardware efficient sparse neural networks

Author: Hagebols, T., 29 Apr 2019

Supervisor: Mocanu, D. (Supervisor 1), Zhang, Y. (Supervisor 2) & Lowet, D. (External coach)

Student thesis: Master

Design and implementation of generic dashboard components for ExSpect

Author: Hoang, A., 31 Dec 1999

Supervisor: Voorhoeve, M. (Supervisor 1), van der Toorn, R. (Supervisor 2) & de Crom, P. (Supervisor 2)

Student thesis: Master