Artem Polyvyanyy
Papers
9
Total Citations
231
H-Index
7
About
Artem Polyvyanyy is a leading researcher at the intersection of **robotic process automation (RPA) and process mining**, a field he has helped define and advance through a body of work collectively known as "Robotic Process Mining." His research addresses one of the most pressing challenges facing organizations today: how to systematically identify, analyze, and automate repetitive human-computer interactions using data-driven methods. Polyvyanyy's most cited work, "Robotic Process Mining: Vision and Challenges" (2020, 125 citations), laid out a compelling research agenda for combining RPA technology with process mining techniques, establishing a conceptual foundation that has since guided the broader community. Building on this vision, he developed practical tools and methods — including the Action Logger system and the Robidium automation framework — that enable organizations to capture user interaction logs and automatically synthesize RPA scripts from them, dramatically reducing the manual effort required for automation. His contributions extend to automated discovery of data transformations and candidate routine identification from unsegmented UI logs, tackling real-world complexity in enterprise automation pipelines. With over 230 cumulative citations across his published works, Polyvyanyy's research has meaningfully shaped how academics and practitioners approach intelligent process automation.
Research Focus
Key Achievements
Top Papers
- 1Robotic Process Mining: Vision and Challenges125 citations · 2020
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- 3Action Logger: Enabling Process Mining for Robotic Process Automation16 citations · 2019
- 4Robotic Process Mining16 citations · 2022
- 5Discovering data transfer routines from user interaction logs15 citations · 2021
- 6Automated Discovery of Data Transformations for Robotic Process Automation13 citations · 2020
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