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D-Index & Metrics

Computer Science

D-Index
58
Citations
17202
World Ranking
3570
National Ranking
106

Overview

Marcello La Rosa is affiliated with the University of Melbourne in Australia. Their research spans key areas in Business, Management and Accounting as well as Computer Science, with substantial contributions in subfields such as Management Information Systems, Information Systems, Management Science and Operations Research, Artificial Intelligence, and Industrial and Manufacturing Engineering.

The primary research topics associated with Marcello La Rosa include Business Process Modeling and Analysis, Service-Oriented Architecture and Web Services, Data Quality and Management, Robotic Process Automation Applications, Big Data and Business Intelligence, Outsourcing and Supply Chain Management, and Time Series Analysis and Forecasting.

Notable recent publications include:

  • "Robotic Process Mining: Vision and Challenges" (2020), published in Business & Information Systems Engineering
  • "AI-augmented Business Process Management Systems: A Research Manifesto" (2023), published in ACM Transactions on Management Information Systems
  • "Opportunities and Challenges for Process Mining in Organizations: Results of a Delphi Study" (2021), published in Business & Information Systems Engineering
  • "Seven Paradoxes of Business Process Management in a Hyper-Connected World" (2020), published in Business & Information Systems Engineering
  • "Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs" (2021), published in Minerva Access (University of Melbourne)

Frequent co-authors collaborating with Marcello La Rosa include Marlon Dumas, Artem Polyvyanyy, Adriano Augusto, Fabrizio Maria Maggi, and Farbod Taymouri.

Publication venues preferred by Marcello La Rosa commonly feature sources such as arXiv (Cornell University), Information Systems, Business & Information Systems Engineering, Zenodo (CERN European Organization for Nuclear Research), and Lecture Notes in Computer Science.

Their book publication record includes a work titled Advanced Information Systems Engineering (2021), released by Springer Science+Business Media.

Best Publications

  • Fundamentals of Business Process Management

    Marlon Dumas;Marcello La Rosa;Jan Mendling;Hajo A. Reijers

  • Process Mining Manifesto

    Wil van der Aalst;Wil van der Aalst;Arya Adriansyah;Ana Karla Alves de Medeiros;Franco Arcieri

  • Blockchains for Business Process Management - Challenges and Opportunities

    Jan Mendling;Ingo Weber;Wil Van Der Aalst;Jan Vom Brocke

  • Predictive Business Process Monitoring with LSTM Neural Networks

    Niek Tax;Ilya Verenich;Marcello La Rosa;Marlon Dumas

  • Automated Discovery of Process Models from Event Logs: Review and Benchmark

    Adriano Augusto;Raffaele Conforti;Marlon Dumas;Marcello La Rosa

  • Outcome-Oriented Predictive Process Monitoring: Review and Benchmark

    Irene Teinemaa;Marlon Dumas;Marcello La Rosa;Fabrizio Maria Maggi

  • Business Process Variability Modeling: A Survey

    Marcello La Rosa;Wil M. P. Van Der Aalst;Marlon Dumas;Fredrik P. Milani

  • CONFIGURABLE WORKFLOW MODELS

    F Florian Gottschalk;Wmp Wil van der Aalst;MH Monique Jansen-Vullers;Marcello La Rosa

  • The Architecture

    Unknown

  • APROMORE : an advanced process model repository

    Marcello La Rosa;Hajo A. Reijers;Wil M.P. van der Aalst;Remco M. Dijkman

  • Configurable multi-perspective business process models

    Marcello La Rosa;Marlon Dumas;Arthur H. M. ter Hofstede;Jan Mendling

  • Business Process Model Merging: An Approach to Business Process Consolidation

    Marcello La Rosa;Marlon Dumas;Reina Uba;Remco Dijkman

  • Split miner: automated discovery of accurate and simple business process models from event logs

    Adriano Augusto;Adriano Augusto;Raffaele Conforti;Marlon Dumas;Marcello La Rosa

  • Editorial: Managing large collections of business process models-Current techniques and challenges

    Remco Dijkman;Marcello La Rosa;Hajo A. Reijers

  • Filtering Out Infrequent Behavior from Business Process Event Logs

    Raffaele Conforti;Marcello La Rosa;Arthur H.M. ter Hofstede

  • Questionnaire-based variability modeling for system configuration

    Marcello La Rosa;Wil M. P. van der Aalst;Wil M. P. van der Aalst;Marlon Dumas;Marlon Dumas;Arthur H. M. ter Hofstede

  • A recommendation system for predicting risks across multiple business process instances

    Raffaele Conforti;Massimiliano de Leoni;Massimiliano de Leoni;Marcello La Rosa;Marcello La Rosa;Wil M.P. van der Aalst;Wil M.P. van der Aalst

  • Process-Aware Information Systems

    Marlon Dumas;Marcello La Rosa;Jan Mendling;Hajo A. Reijers

  • Merging business process models

    Marcello La Rosa;Marlon Dumas;Reina Uba;Remco Dijkman

  • Preserving correctness during business process model configuration

    Wil M. P. van der Aalst;Marlon Dumas;Florian Gottschalk;Arthur H. M. ter Hofstede

  • Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

    Ilya Verenich;Marlon Dumas;Marcello La Rosa;Fabrizio Maria Maggi

  • Business Process Management

    h. c. Wil M. P. van der Aalst;Marcello La Rosa;Marcello La Rosa;Flávia Maria Santoro

  • Blockchains for Business Process Management - Challenges and Opportunities

    Jan Mendling;Ingo Weber;Wil van der Aalst;Jan vom Brocke

Frequent Co-Authors

Marlon Dumas
Marlon Dumas University of Tartu
Arthur H. M. ter Hofstede
Arthur H. M. ter Hofstede Queensland University of Technology
Fabrizio Maria Maggi
Fabrizio Maria Maggi Free University of Bozen-Bolzano
Jan Mendling
Jan Mendling Humboldt-Universität zu Berlin
Wil M. P. van der Aalst
Wil M. P. van der Aalst RWTH Aachen University
Artem Polyvyanyy
Artem Polyvyanyy University of Melbourne
Michael Adams
Michael Adams University of Birmingham
Giancarlo Fortino
Giancarlo Fortino University of Calabria
Michael Rosemann
Michael Rosemann Queensland University of Technology
Jianmin Wang
Jianmin Wang Tsinghua University

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