Christian Stummeyer

Papers

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About

Christian Stummeyer is a leading researcher at the intersection of business process management and intelligent automation. His primary research areas include Robotic Process Automation (RPA), process mining, and the strategic integration of AI in enterprise workflows. Stummeyer’s major contribution lies in bridging the gap between RPA programming and process discovery, particularly through his work on Robotic Process Mining—a methodology that uses data-driven insights to identify and optimize automation opportunities. His most-cited paper, "Decision-Making in Robotic Process Automation Programming and its Influence on Robotic Process Mining" (2024), has garnered 3 citations, reflecting its foundational role in shaping how organizations approach automation design. Beyond this, Stummeyer is recognized for advancing practical frameworks that help businesses move from ad-hoc automation to scalable, evidence-based process improvement. His work is especially valuable for students and practitioners seeking to understand how decision-making in RPA programming directly impacts the efficiency and accuracy of process mining outcomes. By combining technical rigor with real-world applicability, Stummeyer continues to influence both academic discourse and industry best practices in the rapidly evolving field of intelligent automation.