Dr Anna Kalenkova

  • Room: Level: 10 Room: 10.13
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Automata theory. Formal languages
  • Business process modeling and analysis
  • Distributed information systems
  • Formal methods in software engineering
  • Graph theory. Process modeling. Transition systems. Petri nets

Biography

Dr. Anna Kalenkova is a research fellow at the School of Computing and Information Systems, Melbourne School of Engineering, University of Melbourne, Australia. In 2006, she graduated from the Faculty of Computational Mathematics and Cybernetics (Lomonosov Moscow State University) with highest honors. She obtained her first PhD degree in the field of business process analysis at the Institution of Russian Academy of Sciences, Dorodnicyn Computing Centre of RAS in 2011. Then, in 2018, being a research fellow at the Laboratory of Process Aware information Systems, Higher School of Economics (Moscow, Russia), she defended her PhD thesis at Eindhoven University of Technology (Eindhoven, The Netherlands) in the field of process mining under supervision of Prof. Wil van der Aalst and Prof. Irina Lomazova. Her interests lie in business process analysis, including process mining, formal methods and languages, automata theory, and Petri nets.

Recent publications

  1. Kalenkova, A.; Burattin, A.; De Leoni, M.; Van Der Aalst, W.; Sperduti, A. Discovering high-level BPMN process models from event data. Business Process Management Journal. EMERALD GROUP PUBLISHING LTD. 2019, Vol. 25, Issue 5, pp. 995-1019. DOI: 10.1108/BPMJ-02-2018-0051
  2. Polyvyanyy, A.; Kalenkova, A. Monotone Conformance Checking for Partially Matching Designed and Observed Processes. 2019 International Conference on Process Mining (ICPM). IEEE. 2019, pp. 81-88. DOI: 10.1109/ICPM.2019.00022
  3. Tarantsova, P.; Kalenkova, A. Constructing Regular Expressions from Real-life Event Logs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2018, Vol. 11179 LNCS, pp. 274-280. DOI: 10.1007/978-3-030-11027-7_26
  4. Kalenkova, A.; Ageev, A.; Lomazova, I.; Van Der Aalst, W. E-Government Services: Comparing Real and Expected User Behavior. Lecture Notes in Business Information Processing. Springer International Publishing. 2018, Vol. 308, pp. 484-496. DOI: 10.1007/978-3-319-74030-0_38
  5. Kalenkova, A. Learning high-level process models from event data. . 2018.
  6. Konchagin, A.; Kalenkova, A. On the efficient application of Aho-Corasick algorithm in process mining. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2018, Vol. 10716, pp. 371-377. DOI: 10.1007/978-3-319-73013-4_34
  7. Mitsyuk, AA.; Shugurov, IS.; Kalenkova, AA.; Van Der Aalst, WMP. Generating event logs for high-level process models. Simulation Modelling Practice and Theory. ELSEVIER SCIENCE BV. 2017, Vol. 74, pp. 1-16. DOI: 10.1016/j.simpat.2017.01.003
  8. Kalenkova, AA.; Van Der Aalst, WMP.; Lomazova, IA.; Rubin, VA. Process mining using BPMN: relating event logs and process models. Software & Systems Modeling. SPRINGER HEIDELBERG. 2017, Vol. 16, Issue 4, pp. 1019-1048. DOI: 10.1007/s10270-015-0502-0
  9. Shershakov, SA.; Kalenkova, AA.; Lomazova, IA. Transition Systems Reduction: Balancing Between Precision and Simplicity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER INTERNATIONAL PUBLISHING AG. 2017, Vol. 10470, pp. 119-139. DOI: 10.1007/978-3-662-55862-1_6
  10. Shershakov, SA.; Kalenkova, AA.; Lomazova, IA. Transition systems reduction: Balancing between precision and simplicity. CEUR Workshop Proceedings. CEUR Workshop Proceedings. 2016, Vol. 1592, pp. 78-95.
  11. Ivanov, SY.; Kalenkova, AA.; Van Der Aalst, WMP. BPMNDiffViz: A tool for BPMN Models comparison?. CEUR Workshop Proceedings. CEUR Workshop Proceedings. 2015, Vol. 1418, pp. 35-39.
  12. Ivanov, S.; Kalenkova, A. Comparing process models in the BPMN 2.0 XML format. Proceedings of the Institute for System Programming of the RAS. Institute for System Programming of the Russian Academy of Sciences. 2015, Issue 3, pp. 255-266. DOI: 10.15514/ispras-2015-27(3)-17
  13. Van Der Aalst, WMP.; Kalenkova, A.; Rubin, V.; Verbeek, E. Process Discovery Using Localized Events. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER-VERLAG BERLIN. 2015, Vol. 9115, pp. 287-308. DOI: 10.1007/978-3-319-19488-2_15
  14. Kataeva, V.; Kalenkova, A. Applying Graph Grammars for the Generation of Process Models and Their Logs. . Institute for System Programming of the Russian Academy of Sciences. 2014. DOI: 10.15514/syrcose-2014-8-12
  15. Kalenkova, AA.; De Leoni, M.; Van Der Aalst, WMP. Discovering, analyzing and enhancing BPMN models using ProM. CEUR Workshop Proceedings. CEUR Workshop Proceedings. 2014, Vol. 1295, pp. 36-40.
  16. Kalenkova, AA.; Lomazova, IA. Discovery of Cancellation Regions within Process Mining Techniques. Fundamenta Informaticae. IOS PRESS. 2014, Vol. 133, Issue 2-3, pp. 197-209. DOI: 10.3233/FI-2014-1071
  17. Kalenkova, AA.; Lomazova, IA.; Van Der Aalst, WMP. Process model discovery: A method based on transition system decomposition. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2014, Vol. 8489 LNCS, pp. 71-90. DOI: 10.1007/978-3-319-07734-5_5
  18. Mitsyuk, A.; Kalenkova, A.; Sergey, S. Using process mining for the analysis of an e-trade system: A case study. Business Informatics. National Research University Higher School of Economics. 2014, Vol. 29, Issue 3, pp. 15-27.
  19. Kalenkova, AA.; Lomazova, IA. Discovery of cancellation regions within process mining techniques. CEUR Workshop Proceedings. CEUR Workshop Proceedings. 2013, Vol. 1032, pp. 232-244.
  20. Kalenkova, AA. An algorithm of automatic workflow optimization. Programming and Computer Software. MAIK NAUKA/INTERPERIODICA/SPRINGER. 2012, Vol. 38, Issue 1, pp. 43-56. DOI: 10.1134/S0361768812010045

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile