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Contact


Email

marcello.larosa@unimelb.edu.au

Credentials


Position
Honorary Professorial Fellow
School of Computing and Information Systems
Education
Doctoral Degree (Research) / PhD
Queensland University of Technology
Masters Degree (Coursework & Research)
Polytechnic of Turin
ORCID

0000-0001-9568-4035

Prof Marcello La Rosa

Honorary Professorial Fellow
School of Computing and Information Systems

116 Scholarly works
3 Projects

HIGHLIGHTS

  • 2022

    Research grants (ARC, NHMRC, MRFF)

    ARC Research Hub for Digital Bioprocess Development
  • 2019

    Research grants (other domestic)

    Building 4.0 CRC
  • 2019

    Journal article

    Split Miner: Automated Discovery of Accurate and Simple Business Process Models from Event Logs
    DOI: 10.1007/s10115-018-1214-x
  • 2019

    Journal article

    Automated Discovery of Process Models from Event Logs: Review and Benchmark
    DOI: 10.1109/TKDE.2018.2841877
  • 2019

    Journal article

    Local Concurrency Detection in Business Process Event Logs
    DOI: 10.1145/3289181
  • 2018

    Conference Proceedings

    Filtering Spurious Events from Event Streams of Business Processes
    DOI: 10.1007/978-3-319-91563-0_3
  • 2018

    Research Grant

    Diagnosis and Prediction of Business Process Deviances
Marcello La Rosa

Latest Honours,
Awards and Fellowships


2017
Best Demo Paper Award - Int. Conference on Business Process Management - BPM (2017)
2017
Best Paper Award - Int. Conference on Software and System Process - ICSSP (2017)
2017
Distinguished Paper Award - Int. Conference on Advanced Information Systems Engineering - CAiSE (2018)
2017
Best Demo Paper Award - Int. Conference on Advanced Information Systems Engineering - CAiSE (2018)

RECENT SCHOLARLY WORKS

  • 2026

    Book Chapter

    A Digital Twin Framework for Bioprocess Development Using IoT Sensor Data
    DOI: 10.1007/978-3-031-90746-3_12
  • 2025

    Journal article

    Five guidelines to improve context-aware process selection: an Australian banking perspective
    DOI: 10.1108/BPMJ-12-2023-0963
  • 2023

    Journal article

    AI-augmented Business Process Management Systems: A Research Manifesto
    DOI: 10.1145/3576047
  • 2022

    Book Chapter

    Robotic Process Mining
    DOI: 10.1007/978-3-031-08848-3_16
  • 2022

    Journal article

    Measuring Fitness and Precision of Automatically Discovered Process Models: A Principled and Scalable Approach
    DOI: 10.1109/TKDE.2020.3003258
  • 2021

    Journal article

    Opportunities and Challenges for Process Mining in Organizations: Results of a Delphi Study
    DOI: 10.1007/s12599-021-00720-0
  • 2021

    Book

    Grundlagen des Geschäftsprozessmanagements
    DOI: 10.1007/978-3-662-58736-2
  • 2021

    Journal article

    Robotic Process Mining: Vision and Challenges
    DOI: 10.1007/s12599-020-00641-4

Acknowledgement of Country

We acknowledge Aboriginal and Torres Strait Islander people as the Traditional Owners of the unceded lands on which we work, learn and live. We pay respect to Elders past, present and future, and acknowledge the importance of Indigenous knowledge in the Academy.

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