Renuka Sindhgatta

Queensland University of Technology, IBM Research - India

Papers

Total Citations

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About

Renuka Sindhgatta is a researcher specializing in process automation, with a particular focus on Robotic Process Automation (RPA) and hybrid human-machine workflows. Her work sits at the intersection of artificial intelligence, optimization, and enterprise process management, addressing the increasingly complex challenge of designing systems where humans, robotic agents, and intelligent agents collaborate seamlessly. Sindhgatta's most influential contributions center on architecting smarter automation systems. Her 2020 paper on resource-based adaptive RPA (8 citations) demonstrated how automation can be tailored dynamically based on available resources, while her companion work on optimal RPA architectures (5 citations) laid important groundwork for principled design approaches. She has since advanced this line of inquiry through multi-objective evolutionary search methods, applying sophisticated optimization techniques to navigate the trade-offs inherent in agent coordination. More recently, her research has expanded into hybrid automation for knowledge-intensive domains, such as IT operations, exploring how conversational interfaces can bridge human expertise and automated workflows. This work reflects a forward-looking recognition that full end-to-end automation is rarely practical, and that intelligently blending human judgment with robotic efficiency is the more promising frontier. Sindhgatta's growing body of work offers valuable frameworks for practitioners and researchers designing the next generation of intelligent process automation systems.