Simon Siegert

Papers

Total Citations

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About

Simon Siegert is an emerging researcher working at the intersection of artificial intelligence and business process automation, with a particular focus on Robotic Process Automation (RPA) and decision management. His work addresses a critical gap in the RPA landscape: the integration of intelligent decision-making capabilities into traditionally rule-bound automated workflows. In his most recognized contribution, "Adding Decision Management to Robotic Process Automation" (2021), which has garnered 7 citations, Siegert explores how decision management frameworks can enhance the flexibility and intelligence of RPA systems, enabling them to handle more complex, judgment-intensive tasks. This work is complemented by his closely related paper, "Towards Decision Management for Robotic Process Automation" (2021), which lays conceptual groundwork for this integration. Together, these publications signal a forward-thinking research agenda aimed at bridging the gap between deterministic automation and adaptive, decision-aware systems. While still early in his academic career, Siegert's contributions are gaining traction within the process automation and intelligent systems communities, making him a researcher to watch as organizations increasingly seek smarter automation solutions.