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Email

artem.polyvyanyy@unimelb.edu.au

Credentials


Position
Professor
School of Computing and Information Systems
Education
Graduate Certificate
Queensland University of Technology
PhD
University of Potsdam
Masters
Hasso Plattner Institute
Bachelors Degree
National University of Kyiv-Mohyla Academy
ORCID

0000-0002-7672-1643

Prof Artem Polyvyanyy

Professor
School of Computing and Information Systems

170 Scholarly works
6 Projects

HIGHLIGHTS

  • 2023

    Research contracts (non-grants)

    Journey-to-Process Analytics With Agent System Mining
  • 2022

    Research grants (ARC, NHMRC, MRFF)

    ARC Research Hub for Digital Bioprocess Development
  • 2021

    Journal article

    Conformance checking of partially matching processes: An entropy-based approach
    DOI: 10.1016/j.is.2021.101720
  • 2020

    Journal article

    Monotone Precision and Recall Measures for Comparing Executions and Specifications of Dynamic Systems
    DOI: 10.1145/3387909
  • 2018

    Research Grant

    Diagnosis and Prediction of Business Process Deviances
  • 2018

    Report

    Behavioural Quotients for Precision and Recall in Process Mining
  • 2016

    Journal article

    Impact-Driven Process Model Repair
    DOI: 10.1145/2980764
Artem Polyvyanyy

Latest Honours,
Awards and Fellowships


2022
Knowledge and Information Systems Best Paper Award (KAIS)
2021
Best paper, runner up award at the 3rd International Conference on Process Mining (ICPM)
2021
Best paper award at the 40th International Conference on Conceptual Modeling (ER)
2021
Best paper award at the 33rd International Conference on Advanced Information Systems Engineering (CAiSE)

RECENT SCHOLARLY WORKS

  • 2026

    Journal article

    Applying organizational mining to discover agent systems from event data
    DOI: 10.1016/j.is.2025.102669
  • 2026

    Journal article

    SOLID-M: An ontology-aware quality framework for conceptual models discovered from event data
    DOI: 10.1016/j.is.2025.102641
  • 2026

    Book Chapter

    Notes of a Process Scientist: Process Discovery
    DOI: 10.1007/978-3-032-17618-9_26
  • 2026

    Book Chapter

    A Digital Twin Framework for Bioprocess Development Using IoT Sensor Data
    DOI: 10.1007/978-3-031-90746-3_12
  • 2026

    Conference Proceedings

    Multi-Objective Metaheuristics for Effective and Efficient Stochastic Process Discovery
    DOI: 10.1007/978-3-032-02867-9_28
  • 2025

    Journal article

    Correction: Large Process Models: A Vision for Business Process Management in the Age of Generative AI (KI - Künstliche Intelligenz, (2025), 39, 2, (81-95), 10.1007/s13218-024-00863-8)
    DOI: 10.1007/s13218-024-00884-3
  • 2025

    Journal article

    Generalization estimation in process mining: the impact of event data quality
    DOI: 10.1007/s44311-025-00027-3
  • 2025

    Conference Proceedings

    Stochastic Alignments: Matching an Observed Trace to Stochastic Process Models
    DOI: 10.1007/978-3-032-02867-9_12

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