What is he best known for?
The fields of study he is best known for:
- Programming language
- Artificial intelligence
- Machine learning
His primary areas of study are Process mining, Business process, Process modeling, Event and Data mining.
His Process mining study contributes to a more complete understanding of Business process management.
His Business process research is multidisciplinary, incorporating perspectives in Runtime verification, Classifier, Programming language, Database and Data science.
He interconnects Taxonomy, Categorical variable and Benchmark in the investigation of issues within Data science.
His Process modeling study combines topics from a wide range of disciplines, such as Linear temporal logic, Business process discovery and Conformance checking.
Business process discovery is a subfield of Business process modeling that Fabrizio Maria Maggi tackles.
His most cited work include:
- Process Mining Manifesto (684 citations)
- Monitoring business constraints with linear temporal logic: an approach based on colored automata (173 citations)
- Predictive Monitoring of Business Processes (148 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Business process, Process mining, Process modeling, Event and Data mining.
Fabrizio Maria Maggi is interested in Business process modeling, which is a branch of Business process.
He combines subjects such as Machine learning, Business process discovery and Conformance checking with his study of Process mining.
His studies in Process modeling integrate themes in fields like Linear temporal logic, Programming language, Theoretical computer science and Petri net.
His Event research is multidisciplinary, relying on both Range, Field, Set and Temporal logic.
Fabrizio Maria Maggi studied Data mining and Scalability that intersect with Interpretability.
He most often published in these fields:
- Business process (53.80%)
- Process mining (46.74%)
- Process modeling (34.78%)
What were the highlights of his more recent work (between 2018-2021)?
- Business process (53.80%)
- Process mining (46.74%)
- Process modeling (34.78%)
In recent papers he was focusing on the following fields of study:
Fabrizio Maria Maggi mainly investigates Business process, Process mining, Process modeling, Event and Business process modeling.
His Business process study frequently draws connections between related disciplines such as Data science.
The various areas that Fabrizio Maria Maggi examines in his Process mining study include Programming language, State, Artificial intelligence, Machine learning and Software engineering.
His work deals with themes such as Identification, Business Process Model and Notation, User Friendly, Task analysis and Conformance checking, which intersect with Process modeling.
The concepts of his Event study are interwoven with issues in Data modeling, Process, Data mining, Temporal logic and Field.
He is studying Business process discovery, which is a component of Business process modeling.
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)
- Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring (28 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Artificial intelligence
- Machine learning
Fabrizio Maria Maggi spends much of his time researching Business process, Process mining, Process modeling, Event and Process automation system.
His research in the fields of Conformance checking overlaps with other disciplines such as Set and Outcome.
His biological study spans a wide range of topics, including Study software, Machine learning, Software engineering and Artificial intelligence.
Fabrizio Maria Maggi has researched Process modeling in several fields, including Business Process Model and Notation, Business process modeling and Business process discovery.
His Business process modeling research includes elements of Data modeling, Scalability and Task analysis.
His Event research incorporates themes from Process and Data mining.
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