Hajo Reijers – författare

This Festschrift is dedicated to Wil van der Aalst, a leading pioneer in the disciplines of Business Process Management and Process Mining.Wil van der Aalst received an M.Sc. and a Ph.D. at Eindhoven University of Technology during the 1980s. Among other current roles he is a full professor at RWTH Aachen University, leading the Process and Data Science (PADS) group, and he is Chief Scientist at Celonis. His research interests include process mining, data science, Petri nets, process management, workflow management, process modeling, and process analysis. He has over 1000 journal articles and conference papers, he is among the most highly cited computer scientists in the world, and his ideas have influenced researchers, software developers, and standardization committees. Among his achievements and awards Prof. van der Aalst has received honorary degrees from the Moscow Higher School of Economics, Tsinghua University, and Hasselt University. He is an IFIP Fellow, IEEE Fellow, and ACM Fellow, and an elected member of the Royal Netherlands Academy of Arts and Sciences, the Royal Holland Society of Sciences and Humanities, Academia Europaea, the North Rhine-Westphalian Academy of Sciences, Humanities and the Arts, and the German Academy of Science and Engineering.Throughout his career Prof. van der Aalst has collaborated with hundreds of researchers, students, and practitioners, their successes are reflected in the papers contributed to this volume.

This Festschrift is dedicated to Wil van der Aalst, a leading pioneer in the disciplines of Business Process Management and Process Mining.Wil van der Aalst received an M.Sc. and a Ph.D. at Eindhoven University of Technology during the 1980s. Among other current roles he is a full professor at RWTH Aachen University, leading the Process and Data Science (PADS) group, and he is Chief Scientist at Celonis. His research interests include process mining, data science, Petri nets, process management, workflow management, process modeling, and process analysis. He has over 1000 journal articles and conference papers, he is among the most highly cited computer scientists in the world, and his ideas have influenced researchers, software developers, and standardization committees. Among his achievements and awards Prof. van der Aalst has received honorary degrees from the Moscow Higher School of Economics, Tsinghua University, and Hasselt University. He is an IFIP Fellow, IEEE Fellow, and ACM Fellow, and an elected member of the Royal Netherlands Academy of Arts and Sciences, the Royal Holland Society of Sciences and Humanities, Academia Europaea, the North Rhine-Westphalian Academy of Sciences, Humanities and the Arts, and the German Academy of Science and Engineering.Throughout his career Prof. van der Aalst has collaborated with hundreds of researchers, students, and practitioners, their successes are reflected in the papers contributed to this volume.

The two-volume set LNCS 16558 + 16559 constitutes the proceedings of the 38th International Conference on Advanced Information Systems Engineering, CAiSE 2026, which took place in Verona, Italy, during June 2026.The 46 full papers included in the proceedings were carefully reviewed and selected from 331 submissions. The papers were organized in topical sections as follows: Part I: Enterprise Intelligence, Complexity, and Decision Support; Forecasting, Drift, and Prescriptive Process Analytics; Conceptual Modeling, Ontologies, and Value; Enriching Process Mining with Context and Sustainability; Human-in-the-Loop Engineering and Development Practices; Process Discovery and Analysis; Engineering AI Systems across Cloud, Edge, and Cyber-Physical Environments; Part II: LLM-Driven Modeling and Human–AI Collaboration; Agent-Based and Multi-Stakeholder Process Interaction; LLMs and AI for Process Understanding; Predictive and Neuro-Symbolic Process Analytics; Responsible, Fair, and Human-Centered AI; Object-Centric Process Mining and Conformance; Process Mining Data Quality and Repair.

The two-volume set LNCS 16558 + 16559 constitutes the proceedings of the 38th International Conference on Advanced Information Systems Engineering, CAiSE 2026, which took place in Verona, Italy, during June 2026.The 46 full papers included in the proceedings were carefully reviewed and selected from 331 submissions. The papers were organized in topical sections as follows: Part I: Enterprise Intelligence, Complexity, and Decision Support; Forecasting, Drift, and Prescriptive Process Analytics; Conceptual Modeling, Ontologies, and Value; Enriching Process Mining with Context and Sustainability; Human-in-the-Loop Engineering and Development Practices; Process Discovery and Analysis; Engineering AI Systems across Cloud, Edge, and Cyber-Physical Environments; Part II: LLM-Driven Modeling and Human–AI Collaboration; Agent-Based and Multi-Stakeholder Process Interaction; LLMs and AI for Process Understanding; Predictive and Neuro-Symbolic Process Analytics; Responsible, Fair, and Human-Centered AI; Object-Centric Process Mining and Conformance; Process Mining Data Quality and Repair.

The two-volume set LNCS 16558 + 16559 constitutes the proceedings of the 38th International Conference on Advanced Information Systems Engineering, CAiSE 2026, which took place in Verona, Italy, during June 2026.The 46 full papers included in the proceedings were carefully reviewed and selected from 331 submissions. The papers were organized in topical sections as follows: Part I: Enterprise Intelligence, Complexity, and Decision Support; Forecasting, Drift, and Prescriptive Process Analytics; Conceptual Modeling, Ontologies, and Value; Enriching Process Mining with Context and Sustainability; Human-in-the-Loop Engineering and Development Practices; Process Discovery and Analysis; Engineering AI Systems across Cloud, Edge, and Cyber-Physical Environments; Part II: LLM-Driven Modeling and Human–AI Collaboration; Agent-Based and Multi-Stakeholder Process Interaction; LLMs and AI for Process Understanding; Predictive and Neuro-Symbolic Process Analytics; Responsible, Fair, and Human-Centered AI; Object-Centric Process Mining and Conformance; Process Mining Data Quality and Repair.