Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm. - Daniel Schuster 001; Sebastiaan J. van Zelst (BPM, 2020)

Alignment Approximation for Process Trees. - Daniel Schuster 001; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (ICPM Workshops, 2020)

Scalable Online Conformance Checking Using Incremental Prefix-Alignment Computation. - Daniel Schuster 001; Gero Joss Kolhof (ICSOC Workshops, 2020)

Incremental Discovery of Hierarchical Process Models. - Daniel Schuster 001; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (RCIS, 2020)

Cortado - An Interactive Tool for Data-Driven Process Discovery and Modeling. - Daniel Schuster 001; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (Petri Nets, 2021)

Supporting Users in the Continuous Evolution of Automated Routines in Their Smart Spaces. - Estefanía Serral; Daniel Schuster 001; Yannis Bertrand (Business Process Management Workshops, 2021)

Freezing Sub-models During Incremental Process Discovery. - Daniel Schuster 001; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (ER, 2021)

Visualizing Trace Variants from Partially Ordered Event Data. - Daniel Schuster 001; Lukas Schade; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (ICPM Workshops, 2021)

Freezing Sub-Models During Incremental Process Discovery: Extended Version. - Daniel Schuster 001; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (CoRR, 2021)

Temporal Performance Analysis for Block-Structured Process Models in Cortado. - Daniel Schuster 001; Lukas Schade; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (CAiSE Forum, 2022)

Conformance Checking for Trace Fragments Using Infix and Postfix Alignments. - Daniel Schuster 001; Niklas Föcking; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (CoopIS, 2022)

Enhanced Transformation of BPMN Models with Cancellation Features. - Giorgi Lomidze; Daniel Schuster 001; Chiao-Yun Li; Sebastiaan J. van Zelst (EDOC, 2022)

Defining Cases and Variants for Object-Centric Event Data. - Jan Niklas Adams; Daniel Schuster 001; Seth Schmitz; Günther Schuh; Wil M. P. van der Aalst (ICPM, 2022)

A Framework for Extracting and Encoding Features from Object-Centric Event Data. - Jan Niklas Adams; Gyunam Park; Sergej Levich; Daniel Schuster 001; Wil M. P. van der Aalst (ICSOC, 2022)

Control-Flow-Based Querying of Process Executions from Partially Ordered Event Data. - Daniel Schuster 001; Michael Martini; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (ICSOC, 2022)

A Generic Trace Ordering Framework for Incremental Process Discovery. - Daniel Schuster 001; Emanuel Domnitsch; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (IDA, 2022)

Utilizing domain knowledge in data-driven process discovery: A literature review. - Daniel Schuster 001; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (Comput. Ind., 2022)

Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case Study. - Alessandro Berti 001; Daniel Schuster 001; Wil M. P. van der Aalst (Business Process Management Workshops, 2023)

Incremental Discovery of Process Models Using Trace Fragments. - Daniel Schuster 001; Niklas Föcking; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (BPM, 2023)

Scalable Discovery of Partially Ordered Workflow Models with Formal Guarantees. - Humam Kourani; Daniel Schuster 001; Wil M. P. van der Aalst (ICPM, 2023)

Mining Frequent Infix Patterns from Concurrency-Aware Process Execution Variants. - Michael Martini; Daniel Schuster 001; Wil M. P. van der Aalst (Proc. VLDB Endow., 2023)

Cortado: A dedicated process mining tool for interactive process discovery. - Daniel Schuster 001; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (SoftwareX, 2023)

PM4Py: A process mining library for Python. - Alessandro Berti 001; Sebastiaan J. van Zelst; Daniel Schuster 001 (Softw. Impacts, 2023)

Pattern-based action engine: Generating process management actions using temporal patterns of process-centric problems. - Gyunam Park; Daniel Schuster 001; Wil M. P. van der Aalst (Comput. Ind., 2023)

Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, and Evaluation Strategies. - Alessandro Berti 001; Humam Kourani; Hannes Häfke; Chiao-Yun Li; Daniel Schuster 001 (BPMDS/EMMSAD@CAiSE, 2024)

Process Modeling with Large Language Models. - Humam Kourani; Alessandro Berti 001; Daniel Schuster 001; Wil M. P. van der Aalst (BPMDS/EMMSAD@CAiSE, 2024)

ProMoAI: Process Modeling with Generative AI. - Humam Kourani; Alessandro Berti 001; Daniel Schuster 001; Wil M. P. van der Aalst (IJCAI, 2024)

Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, Evaluation Strategies, and Future Challenges. - Alessandro Berti 001; Humam Kourani; Hannes Häfke; Chiao-Yun Li; Daniel Schuster 001 (CoRR, 2024)

Leveraging Large Language Models for Enhanced Process Model Comprehension. - Humam Kourani; Alessandro Berti 001; Jasmin Henrich; Wolfgang Kratsch; Robin Weidlich; Chiao-Yun Li; Ahmad Arslan; Daniel Schuster 001; Wil M. P. van der Aalst (CoRR, 2024)

Evaluating Large Language Models on Business Process Modeling: Framework, Benchmark, and Self-Improvement Analysis. - Humam Kourani; Alessandro Berti 001; Daniel Schuster 001; Wil M. P. van der Aalst (CoRR, 2024)

Incremental process discovery. - Daniel Schuster 001 (2024)

Defining and visualizing process execution variants from partially ordered event data. - Daniel Schuster 001; Francesca Zerbato; Sebastiaan J. van Zelst; Wil M. P. van der Aalst (Inf. Sci., 2024)

Analyzing Healthcare Processes with Incremental Process Discovery: Practical Insights from a Real-World Application. - Daniel Schuster 001; Elisabetta Benevento; Davide Aloini; Wil M. P. van der Aalst (J. Heal. Informatics Res., 2024)

Incremental Process Discovery - Daniel Schuster 001 (Springer, 2025)

Computing Alignments for Partially-Ordered Traces Through Petri Net Unfoldings. - Ariba Siddiqui; Wil M. P. van der Aalst; Daniel Schuster 001 (Petri Nets, 2025)

Discovering partially ordered workflow models. - Humam Kourani; Sebastiaan J. van Zelst; Daniel Schuster 001; Wil M. P. van der Aalst (Inf. Syst., 2025)