Teaching Strengths
Dr Anna Kalenkova
Lecturer
School of Computer Science and Information Technology
College of Engineering and Information Technology
Eligible to supervise Masters and PhD - email supervisor to discuss availability.
I have a background in theoretical computer science and applied mathematics. My interests lie in process mining, event data analysis, visual analytics, and information theory. I apply stochastic modelling in process mining to study how stochastic models can be discovered from event data.
| Date | Position | Institution name |
|---|---|---|
| 2023 - ongoing | Lecturer | University of Adelaide |
| 2022 - 2023 | Postdoctoral Research Fellow | University of Adelaide |
| 2019 - 2021 | Postdoctoral Research Fellow | University of Melbourne |
| Year | Citation |
|---|---|
| 2026 | Tour, A., Polyvyanyy, A., & Kalenkova, A. (2026). SOLID-M: An ontology-aware quality framework for conceptual models discovered from event data. Information Systems, 137, 14 pages. |
| 2025 | Kalenkova, A., Mitchell, L., & Roughan, M. (2025). Performance Analysis: Discovering Semi-Markov Models From Event Logs. IEEE Access, 13, 38035-1-38053-19. Scopus1 WoS1 |
| 2024 | Yavorskiy, R., Cavalli, A. R., & Kalenkova, A. (2024). Preface. Communications in Computer and Information Science, 1559, v. |
| 2022 | Polyvyanyy, A., & Kalenkova, A. (2022). Conformance checking of partially matching processes: An entropy-based approach. Information Systems, 106, 1-15. Scopus9 WoS6 |
| 2021 | Tour, A., Polyvyanyy, A., & Kalenkova, A. (2021). Agent system mining: Vision, benefits, and challenges. IEEE Access, 9, 99480-99494. Scopus24 WoS17 |
| 2021 | Kalenkova, A., Carmona, J., Polyvyanyy, A., & La Rosa, M. (2021). Automated Repair of Process Models with Non-local Constraints Using State-Based Region Theory. Fundamenta Informaticae, 183(3-4), 293-317. Scopus2 WoS1 |
| 2019 | Kalenkova, A. A., & Kolesnikov, D. A. (2019). Application of a Genetic Algorithm for Finding Edit Distances between Process Models. Automatic Control and Computer Sciences, 53(7), 617-627. Scopus2 |
| 2019 | Kalenkova, A., Burattin, A., de Leoni, M., van der Aalst, W., & Sperduti, A. (2019). Discovering high-level BPMN process models from event data. Business Process Management Journal, 25(5), 995-1019. Scopus17 WoS12 |
| 2017 | Mitsyuk, A. A., Shugurov, I. S., Kalenkova, A. A., & van der Aalst, W. M. P. (2017). Generating event logs for high-level process models. Simulation Modelling Practice and Theory, 74, 1-16. Scopus26 WoS19 |
| 2017 | Kalenkova, A. A., van der Aalst, W. M. P., Lomazova, I. A., & Rubin, V. A. (2017). Process mining using BPMN: relating event logs and process models. Software and Systems Modeling, 16(4), 1019-1048. Scopus75 WoS51 |
| 2014 | Mitsyuk, A., Kalenkova, A., Shershakov, S., & van der Aalst, W. (2014). USING PROCESS MINING FOR THE ANALYSIS OF AN E-TRADE SYSTEM: A CASE STUDY. BIZNES INFORMATIKA-BUSINESS INFORMATICS, 29(3), 15-27. WoS3 |
| 2012 | Kalenkova, A. A. (2012). An algorithm of automatic workflow optimization. Programming and Computer Software, 38(1), 43-56. Scopus2 WoS1 |
| 2010 | Kalenkova, A. A. (2010). Application of if-conversion to verification and optimization of workflows. Programming and Computer Software, 36(5), 276-288. Scopus3 WoS3 |
| - | Kalenkova, A. A., & Kolesnikov, D. A. (2018). Application of Genetic Algorithms for Finding Edit Distance between Process Models. Modeling and Analysis of Information Systems, 25(6), 711-725. |
| Year | Citation |
|---|---|
| 2021 | van der Aalst, W. M. P., Batagelj, V., Buzmakov, A., Ignatov, D. I., Kalenkova, A., Khachay, M., . . . Tutubalina, E. (2021). Preface (Vol. 1357 CCIS). |
| 2021 | Kalenkova, A., Lozano, J., & Yavorskiy, R. (2021). Preface (Vol. 1288 CCIS). |
| 2021 | van der Aalst, W. M. P., Batagelj, V., Buzmakov, A., Ignatov, D., Kalenkova, A., Khachay, M., . . . Tutubalina, E. (2021). Preface (Vol. 12602 LNCS). W. van der Aalst, E. Best, & W. Penczek (Eds.), SAGE Publications. DOI |
| Year | Citation |
|---|---|
| 2017 | Shershakov, S. A., Kalenkova, A. A., & Lomazova, I. A. (2017). Transition systems reduction: Balancing between precision and simplicity. In M. Koutny, J. Kleijn, & W. Penczek (Eds.), Transactions on Petri Nets and Other Models of Concurrency XII (Vol. 10470, pp. 119-139). Berlin, Heidelbert: Springer. DOI |
| Year | Citation |
|---|---|
| 2024 | Montali, M., Kalenkova, A., & Senderovich, A. (2024). Stochastic Modeling for Business Process Management. In A. Marrella, M. Resinas, M. Jans, & M. Rosemann (Eds.), BUSINESS PROCESS MANAGEMENT, BPM 2024 Vol. 14940 (pp. 541-543). POLAND, AGH Univ Krakow, Krakow: SPRINGER INTERNATIONAL PUBLISHING AG. |
| 2023 | Tour, A., Polyvyanyy, A., Kalenkova, A., & Senderovich, A. (2023). Agent Miner: An Algorithm for Discovering Agent Systems from Event Data. In G. Goos (Ed.), Proceedings of the 21st International Conference on Business Process Management (BPM 2023), as published in Lecture Notes in Computer Science Vol. 14159 (pp. 284-302). Cham, Switzerland: Springer Nature. DOI Scopus10 WoS6 |
| 2021 | Jans, M., Janssenswillen, G., Kalenkova, A., & Maggi, F. M. (2021). Preface to the ICPM 2021 Doctoral Consortium and Tool Demonstration Track. In CEUR Workshop Proceedings Vol. 3098. |
| 2021 | Kalenkova, A., Polyvyanyy, A., & Rosa, M. L. (2021). Structural and Behavioral Biases in Process Comparison Using Models and Logs. In Proceedings of the International Conference on Conceptual Modeling (CCM 2021), as published in Lecture Notes in Computer Science Vol. 13011 (pp. 62-73). Cham, Switzerland: Springer International Publishing. DOI Scopus2 WoS1 |
| 2020 | Polyvyanyy, A., Alkhammash, H., Di Ciccio, C., García-Bañuelos, L., Kalenkova, A., Leemans, S. J. J., . . . Weidlich, M. (2020). Entropia: A family of entropy-based conformance checking measures for process mining. In CEUR Workshop Proceedings Vol. 2703 (pp. 39-42). RWTH Aachen University: CEUR-WS. Scopus9 |
| 2020 | Kalenkova, A., & Polyvyanyy, A. (2020). A spectrum of entropy-based precision and recall measurements between partially matching designed and observed processes. In Service-Oriented Computing: 18th International Conference, ICSOC 2020, Dubai, United Arab Emirates, December 14–17, 2020, Proceedings Vol. 12571 LNCS (pp. 337-354). Switzerland: Springer International Publishing. DOI Scopus7 WoS5 |
| 2020 | Kalenkova, A., Polyvyanyy, A., & La Rosa, M. (2020). A framework for estimating simplicity of automatically discovered process models based on structural and behavioral characteristics. In Proceedings of the 18th International Conference, Business Process Management (BPM 2020) as published in Lecture Notes in Computer Science Vol. 12168 LNCS (pp. 129-146). New York, NY, USA: Springer International Publishing. DOI Scopus5 WoS5 |
| 2020 | Kalenkova, A., Carmona, J., Polyvyanyy, A., & La Rosa, M. (2020). Automated Repair of Process Models Using Non-local Constraints. In Proceedings of the 41st International Conference on Applications and Theory of Petri Nets and Concurrency (PETRI NETS 2020), as published in Lecture Notes in Computer Science Vol. 12152 LNCS (pp. 280-300). Manhattan, New York City, USA: Springer International Publishing. DOI Scopus8 WoS9 |
| 2019 | Skobtsov, A., & Kalenkova, A. (2019). Efficient algorithms for finding differences between process models. In 2019 Ivannikov Ispras Open Conference, (ISPRAS) (pp. 60-66). Piscataway, New Jersey, USA: IEEE. DOI Scopus5 |
| 2019 | Skobtsov, A. V., & Kalenkova, A. A. (2019). Using heuristic algorithms for fast alignment between business processes and goals. In Proceedings 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW) Vol. 2019-October (pp. 85-91). Piscataway, NJ, USA: IEEE. DOI Scopus1 |
| 2019 | Skobtsov, A. V., & Kalenkova, A. A. (2019). Efficient comparison of process models using Tabu search algorithm. In I. Lomazova, A. Kalenkova, & R. Yavorsky (Eds.), Proceedings of the MACSPro Workshop 2019 (MACSPro 2019) Vol. 2478 (pp. 51-61). Aachen, Germany: CEUR. Scopus1 |
| 2019 | Polyvyanyy, A., & Kalenkova, A. (2019). Monotone conformance checking for partially matching designed and observed processes. In Proceedings - 2019 International Conference on Process Mining, ICPM 2019 (pp. 81-88). Piscataway, New Jersey, NJ, USA: IEEE. DOI Scopus19 WoS16 |
| 2018 | Tarantsova, P. D., & Kalenkova, A. A. (2018). Constructing regular expressions from real-life event logs. In W. M. P. van der Aalst, V. Batagelj, G. Glavas, D. I. Ignatov, M. Khachay, & S. O. Kuznetsov (Eds.), Conference proceedings Analysis of Images, Social Networks and Texts Vol. 11179 LNCS (pp. 274-280). Switzerland: Springer International Publishing. DOI |
| 2018 | Kalenkova, A. A., Ageev, A. A., Lomazova, I. A., & van der Aalst, W. M. P. (2018). E-government services: Comparing real and expected user behavior. In E. Teniente, & M. Weidlich (Eds.), Business Process Management Workshops Vol. 308 (pp. 484-496). New York City, USA: Springer International Publishing. DOI Scopus12 WoS5 |
| 2018 | Konchagin, A. M., & Kalenkova, A. A. (2018). On the efficient application of aho-corasick algorithm in process mining. In Conference proceedings Analysis of Images, Social Networks and Texts Vol. 10716 LNCS (pp. 371-377). Switzerland: Springer International Publishing. DOI |
| 2017 | Shershakov, S. A., Kalenkova, A. A., & Lomazova, I. A. (2017). Transition systems reduction: Balancing between precision and simplicity. In Transactions on Petri Nets and Other Models of Concurrency XII Vol. 10470 LNCS (pp. 119-139). Berlin Heidelberg: Springer. DOI Scopus3 WoS1 |
| 2016 | Kalenkova, A. A., van der Aalst, W. M. P., Lomazova, I. A., & Rubin, V. A. (2016). Process Mining Using BPMN: Relating Event Logs and Process Models. In 19TH ACM/IEEE INTERNATIONAL CONFERENCE ON MODEL DRIVEN ENGINEERING LANGUAGES AND SYSTEMS (MODELS'16) (pp. 123). FRANCE, Saint Malo: ASSOC COMPUTING MACHINERY. DOI WoS4 |
| 2015 | Ivanov, S. Y., Kalenkova, A. A., & Van Der Aalst, W. M. P. (2015). BPMNDiffViz: A tool for BPMN Models comparison?. In Ceur Workshop Proceedings Vol. 1418 (pp. 35-39). Scopus26 |
| 2015 | Van Der Aalst, W. M. P., Kalenkova, A., Rubin, V., & Verbeek, E. (2015). Process discovery using localized events. In R. Devillers, & A. Valmari (Eds.), Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics Vol. 9115 (pp. 287-308). Brussels, BELGIUM: SPRINGER-VERLAG BERLIN. DOI Scopus24 WoS19 |
| 2014 | Kalenkova, A. A., De Leoni, M., & Van Der Aalst, W. M. P. (2014). Discovering, analyzing and enhancing BPMN models using ProM. In Ceur Workshop Proceedings Vol. 1295 (pp. 36-40). Scopus20 |
| 2014 | Kalenkova, A. A., & Lomazova, I. A. (2014). Discovery of cancellation regions within process mining techniques. In Fundamenta Informaticae Vol. 133 (pp. 197-209). IOS PRESS. DOI Scopus14 WoS9 |
| 2014 | Kalenkova, A. A., Lomazova, I. A., & Van Der Aalst, W. M. P. (2014). Process model discovery: A method based on transition system decomposition. In Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics Vol. 8489 LNCS (pp. 71-90). Springer International Publishing. DOI Scopus19 |
| 2013 | Kalenkova, A. A., & Lomazova, I. A. (2013). Discovery of cancellation regions within process mining techniques. In CEUR Workshop Proceedings Vol. 1032 (pp. 232-244). Scopus4 |
| 2011 | Ataeva, O. M., Kalenkova, A. A., & Serebriakov, V. A. (2011). MultiMeta - A system of spatial and digital library resources integration. In CEUR Workshop Proceedings Vol. 803 (pp. 26-29). |
| Year | Citation |
|---|---|
| 2025 | Kalenkova, A., Mitchell, L., & Johnson, E. (2025). Discovering Coordinated Processes From Social Online Networks. |
| 2022 | Kalenkova, A., Mitchell, L., & Roughan, M. (2022). Performance Analysis: Discovering Semi-Markov Models From Event Logs. |
2025 Freiburg - Adelaide Partnership Fund grant.
Semester 2 2025
Algorithms and Data Structure Analysis (COMP SCI 2201/7201)
Event Driven Computing (COMP SCI 7611/7411/4811/4411)
Advanced Mathematical Perspectives III (MATH 3020)
Semester 1 2025
Algorithms and Data Structure Analysis (COMP SCI 2201/7201)
Semester 2 2024
Algorithm Design and Data Structures (COMP SCI 2103)
Algorithms and Data Structure Analysis (COMP SCI 2201/7201)
Event Driven Computing (COMP SCI 7411/4811/4411)
Advanced Mathematical Perspectives III (MATH 3020)
Semester 1 2024
Algorithm Design and Data Structures (COMP SCI 2103)
Semester 2 2023
Algorithm Design and Data Structures (COMP SCI 2103)
Event Driven Computing (COMP SCI 7411/4811/4411)
Advanced Mathematical Perspectives III (MATH 3020)
Semester 1 2023
Algorithm Design and Data Structures (COMP SCI 2103)
Event Driven Computing (COMP SCI 7411/4811/4411)
Advanced Mathematical Perspectives III (MATH 3020)
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2024 | Co-Supervisor | Developing explainable AI methods for the financial sector | Doctor of Philosophy | Doctorate | Full Time | Mr Wenrui Zhang |
| 2024 | Co-Supervisor | Developing explainable AI methods for the financial sector | Doctor of Philosophy | Doctorate | Full Time | Mr Wenrui Zhang |
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2023 - 2025 | Principal Supervisor | Process Discovery and Classification of User Behaviours in Online Social Networks | Master of Philosophy | Master | Full Time | Mr Ethan Michael Johnson |
| 2022 - 2023 | Co-Supervisor | Measuring and modelling information flows in real-world networks | Master of Philosophy | Master | Full Time | Miss Bridget Anna Smart |
| 2022 - 2024 | Co-Supervisor | A multi-dimensional extension of the Elo rating system | Doctor of Philosophy | Doctorate | Full Time | Mr Adam Hugh Hamilton |
| Date | Role | Committee | Institution | Country |
|---|---|---|---|---|
| 2026 - 2026 | Chair | International Conference on Application and Theory of Petri Nets and Concurrency (ATPN) | International Conference on Application and Theory of Petri Nets and Concurrency (ATPN) | Germany |
| 2025 - 2026 | Member | International Conference on Business Process Modeling, Development, and Support (BPMDS) | International Conference on Business Process Modeling, Development, and Support (BPMDS) | Australia |
| 2025 - 2025 | Member | Workshop: Generative AI for Process Mining (co-located with ICPM) | Workshop: Generative AI for Process Mining (co-located with ICPM) | Australia |
| 2022 - 2024 | Member | International Workshop on Data-Driven Business Process Optimization (BPO) | International Workshop on Data-Driven Business Process Optimization (BPO) | Australia |
| 2022 - 2022 | Member | International Workshop on Computational Intelligence for Process Mining | International Workshop on Computational Intelligence for Process Mining | Australia |
| 2022 - 2022 | Member | International Conference on Application and Theory of Petri Nets and Concurrency (ATPN), Tool Session | International Conference on Application and Theory of Petri Nets and Concurrency (ATPN), Tool Session | Australia |
| 2020 - 2025 | Member | Workshop on Process Querying, Manipulation and Intelligence (PQMI) | Workshop on Process Querying, Manipulation and Intelligence (PQMI) | Australia |
| 2020 - 2025 | Member | International Conference on Process Mining (ICPM) | International Conference on Process Mining (ICPM) | Australia |
| 2020 - 2025 | Member | International Conference on Business Process Management (BPM) | International Conference on Business Process Management (BPM) | Australia |
| 2015 - 2025 | Member | Workshop on Algorithms and Theories for the Analysis of Event Data (ATAED) | Workshop on Algorithms and Theories for the Analysis of Event Data (ATAED) | Australia |
| 2015 - 2024 | Member | Business Process Intelligence Workshop (BPI) | Business Process Intelligence Workshop (BPI) | Australia |
| Date | Role | Editorial Board Name | Institution | Country |
|---|---|---|---|---|
| 2022 - 2024 | Associate Editor | CEUR Workshop Proceedings (CEUR-WS.org) | CEUR Workshop Proceedings (CEUR-WS.org) | Germany |
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