What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Software
His scientific interests lie mostly in Business process, Process modeling, Business process modeling, Business process management and Business process discovery.
The concepts of his Business process study are interwoven with issues in Database and Data science.
His biological study spans a wide range of topics, including Software engineering and Data mining.
His work in the fields of Business process modeling, such as Business Process Model and Notation and Artifact-centric business process model, overlaps with other areas such as Multiple Models.
His study in Business process management is interdisciplinary in nature, drawing from both Knowledge management, Machine learning and Artificial intelligence.
His research investigates the connection with Business process discovery and areas like Process mining which intersect with concerns in Business intelligence.
His most cited work include:
- Process Mining Manifesto (684 citations)
- Fundamentals of Business Process Management (508 citations)
- Blockchains for Business Process Management - Challenges and Opportunities (230 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Business process, Process modeling, Process, Process mining and Business process modeling.
His work in Business process covers topics such as Process which are related to areas like Real-time computing.
His Process modeling study integrates concerns from other disciplines, such as Petri net, Business process discovery, Concurrency, Business Process Model and Notation and Software engineering.
The study incorporates disciplines such as Domain, Systems engineering, Reference model and Data science in addition to Process.
His work deals with themes such as Scalability, Data mining, Artificial intelligence, Event and Machine learning, which intersect with Process mining.
His work on Artifact-centric business process model as part of general Business process modeling study is frequently linked to Set, bridging the gap between disciplines.
He most often published in these fields:
- Business process (57.55%)
- Process modeling (51.02%)
- Process (46.53%)
What were the highlights of his more recent work (between 2018-2021)?
- Event (29.80%)
- Business process (57.55%)
- Process mining (46.94%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Event, Business process, Process mining, Process modeling and Process.
His research integrates issues of Process, Data mining, Timestamp, Artificial intelligence and Machine learning in his study of Event.
The Business process study which covers Data science that intersects with Taxonomy.
Business process modeling covers Marcello La Rosa research in Process mining.
The concepts of his Process modeling study are interwoven with issues in Scalability, Field, Business process discovery, Concurrency and Conformance checking.
In general Process study, his work on Business process management often relates to the realm of Noise and Process automation system, thereby connecting several areas of interest.
Between 2018 and 2021, his most popular works were:
- Automated Discovery of Process Models from Event Logs: Review and Benchmark (115 citations)
- Outcome-Oriented Predictive Process Monitoring: Review and Benchmark (58 citations)
- Split Miner: Automated Discovery of Accurate and Simple Business Process Models from Event Logs (50 citations)
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