Prof.dr.ir. Wil van der Aalst is a
full professor at RWTH Aachen University leading the Process and Data Science
(PADS) group. He is also part-time affiliated with the Fraunhofer-Institut für
Angewandte Informationstechnik (FIT) where he leads FIT's Process Mining group
and the Technische Universiteit Eindhoven (TU/e). Until December 2017, he was
the scientific director of the Data Science Center Eindhoven (DSC/e) and led
the Architecture of Information Systems group at TU/e. Since 2003, he holds a
part-time position at Queensland University of Technology (QUT). Currently, he
is also a distinguished fellow of Fondazione Bruno Kessler (FBK) in Trento and
a member of the Board of Governors of Tilburg University. His research
interests include process mining, Petri nets, business process management,
workflow management, process modeling, and process analysis. Wil van der Aalst
has published over 220 journal papers, 20 books (as author or editor), 500
refereed conference/workshop publications, and 75 book chapters. Many of his
papers are highly cited (he one of the most cited computer scientists in the
world; according to Google Scholar, he has an H-index of 142 and has been cited
over 92,000 times) and his ideas have influenced researchers, software
developers, and standardization committees working on process support. Next to
serving on the editorial boards of over ten scientific journals, he is also
playing an advisory role for several companies, including Fluxicon, Celonis,
Processgold, and Bright Cape. Van der Aalst received honorary degrees from the
Moscow Higher School of Economics (Prof. h.c.), Tsinghua University, and
Hasselt University (Dr. h.c.). He is also an elected member of the Royal
Netherlands Academy of Arts and Sciences, the Royal Holland Society of Sciences
and Humanities, and the Academy of Europe. In 2018, he was awarded an
Alexander-von-Humboldt Professorship.
Unlocking the full potential of process mining starts with preparing your enterprise data. Process mining analyzes vast datasets to reveal inefficiencies and opportunities for optimization, helping organizations enhance operational efficiency, cut costs, and boost customer satisfaction.
In this session we will discuss how to get your data ready for process mining to be effective through quality, efficiency and standardisation to enable actionable insights.
In this session, we are joined by a panel of experts to: