Dr Artem Polyvyanyy

  • Room: Level: 10 Room: 15
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Computation Theory
  • Computation Theory
  • Distributed Computing (Distributed Systems)
  • Distributed Computing (Petri Nets)
  • Information Systems (Business Intelligence)
  • Information Systems (Business Process Management)
  • Information Systems (Decision Support Systems)
  • Information Systems (Process Mining)
  • Software Engineering (Process Querying)

Personal webpage

http://polyvyanyy.com/

Biography

Dr. Artem Polyvyanyy is a senior lecturer at the School of Computing and Information Systems, Melbourne School of Engineering, at the University of Melbourne, Melbourne, Australia. He has a strong background in Computer Science, Software Engineering, and Business Process Management from the National University of Kyiv-Mohyla Academy, Kyiv, Ukraine, and the Hasso Plattner Institute, Potsdam, Germany. In March 2012, he received a Ph.D. degree (Dr. rer. nat.) in the scientific discipline of Practical Computer Science from the University of Potsdam, Germany. Artem's industry experience includes internships at Wincor-Nixdorf GmbH in Hamburg, Germany, and SAP Labs in Palo Alto, CA, USA. His research and teaching interests include Distributed and Parallel Systems, Automata Theory, Formal Methods, Information Systems, Software Engineering, and Workflow Management. More recently, he has conducted research on the fundamentals of process analysis, the foundations of behavior abstraction in concurrent systems, and querying of process model repositories.

Recent publications

  1. Polyvyanyy, A.; Pika, A.; Wynn, MT.; Ter Hofstede, AHM. A systematic approach for discovering causal dependencies between observations and incidents in the health and safety domain. Safety Science. Elsevier BV. 2019, Vol. 118, pp. 345-354. DOI: 10.1016/j.ssci.2019.04.045
  2. Van Der Werf, JMEM.; Polyvyanyy, A. An Assignment on Information System Modeling: On Teaching Data and Process Integration. Lecture Notes in Business Information Processing. Springer International Publishing. 2019, Vol. 342, pp. 553-566. DOI: 10.1007/978-3-030-11641-5_44
  3. Polyvyanyy, A.; Van Der Werf, JMEM.; Overbeek, S.; Brouwers, R. Information Systems Modeling: Language, Verification, and Tool Support. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2019, Vol. 11483 LNCS, pp. 194-212. DOI: 10.1007/978-3-030-21290-2_13
  4. Polyvyanyy, A.; Van Der Werf, JM.; Overbeek, S.; Brouwers, R. Information Systems Modeling: Language, Verification, and Tool Support. . Springer. 2019, pp. 194-212. DOI: 10.1007/978-3-030-21290-2
  5. Polyvyanyy, A.; Kalenkova, A. Monotone Conformance Checking for Partially Matching Designed and Observed Processes. . IEEE. 2019.
  6. Burattin, A.; Polyvyanyy, A.; Van Zelst, SJ. Preface. CEUR Workshop Proceedings. 2019, Vol. 2374.
  7. Leno, V.; Polyvyanyy, A.; La Rosa, M.; Dumas, M.; Maggi, F. Robotic Process Mining: Vision and Challenges. Business and Information Systems Engineering. Springer Verlag. 2019.
  8. Augusto, A.; Conforti, R.; Dumas, M.; La Rosa, M.; Polyvyanyy, A. Split miner: automated discovery of accurate and simple business process models from event logs. Knowledge and Information Systems. SPRINGER LONDON LTD. 2019, Vol. 59, Issue 2, pp. 251-284. DOI: 10.1007/s10115-018-1214-x
  9. Polyvyanyy, A.; Solti, A.; Weidlich, M.; Di Ciccio, C.; Mendling, J. Behavioural Quotients for Precision and Recall in Process Mining. . 2018.
  10. Polyvyanyy, A. Business Process Querying. . SpringerLink. 2018, pp. 1-9. DOI: 10.1007/978-3-319-63962-8_108-1
  11. De Alwis, AAC.; Barros, A.; Fidge, C.; Polyvyanyy, A. Discovering microservices in enterprise systems using a business object containment heuristic. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SpringerLink. 2018, Vol. 11230 LNCS, pp. 60-79. DOI: 10.1007/978-3-030-02671-4_4
  12. De Alwis, AAC.; Barros, A.; Polyvyanyy, A.; Fidge, C. Function-splitting heuristics for discovery of microservices in enterprise systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Nature Switzerland. 2018, Vol. 11236 LNCS, pp. 37-53. DOI: 10.1007/978-3-030-03596-9_3
  13. Polyvyanyy, A.; Suermeli, J.; Weidlich, M. Interleaving isotactics - An equivalence notion on behaviour abstractions. Theoretical Computer Science. ELSEVIER SCIENCE BV. 2018, Vol. 737, pp. 1-18. DOI: 10.1016/j.tcs.2018.01.005
  14. Poll, R.; Polyvyanyy, A.; Rosemann, M.; Röglinger, M.; Rupprecht, L. Process forecasting: Towards proactive business process management. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Nature Switzerland. 2018, Vol. 11080 LNCS, pp. 496-512. DOI: 10.1007/978-3-319-98648-7_29
  15. Nolte, A.; Brown, R.; Anslow, C.; Wiechers, M.; Polyvyanyy, A.; Herrmann, T. Collaborative business process modeling in multi-surface environments. . Springer International Publishing. 2017, pp. 259-286. DOI: 10.1007/978-3-319-45853-3_12
  16. Polyvyanyy, A.; Van Der Aalst, WMP.; Ter Hofstede, AHM.; Wynn, MT. Impact-Driven Process Model Repair. ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY. ASSOC COMPUTING MACHINERY. 2017, Vol. 25, Issue 4. DOI: 10.1145/2980764
  17. Polyvyanyy, A.; Ouyang, C.; Barros, A.; Van Der Aalst, WMP. Process querying: Enabling business intelligence through query-based process analytics. Decision Support Systems. ELSEVIER SCIENCE BV. 2017, Vol. 100, pp. 41-56. DOI: 10.1016/j.dss.2017.04.011
  18. Polyvyanyy, A.; Armas-cervantes, A.; Dumas, M.; Garcia-banuelos, L. On the expressive power of behavioral profiles. Formal Aspects of Computing. SPRINGER. 2016, Vol. 28, Issue 4, pp. 597-613. DOI: 10.1007/s00165-016-0372-4
  19. Armas-cervantes, A.; Dumas, M.; Polyvyanyy, A. On the suitability of generalized behavioral profiles for process model comparison. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science. 2016, Vol. 9421, pp. 13-28. DOI: 10.1007/978-3-319-33612-1_2
  20. Leopold, H.; Mendling, J.; Polyvyanyy, A. Supporting process model validation through natural language generation. Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI). Gesellschaft fur Informatik (GI). 2016, Vol. P252, pp. 71-72.

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