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About

Hoa Khanh Dam is a researcher whose work sits at the intersection of intelligent automation, multi-agent systems, and evolutionary computation. His research has made meaningful contributions to the emerging field of Robotic Process Automation (RPA), where he has tackled one of its most pressing challenges: designing optimal architectures that enable seamless coordination between human agents, robotic agents, and intelligent agents. His 2020 paper on designing optimal RPA architectures and its 2021 companion exploring the future of RPA have each garnered five citations, establishing him as an early voice in shaping how organizations approach automation strategy. His 2024 work applies multi-objective evolutionary search to RPA architecture optimization, reflecting a sophisticated blend of AI and software engineering principles. Beyond automation, Dam has contributed to the broader field of multi-agent systems, serving as a special issue editor on principles and practices in the domain, acknowledging the foundational role of agent-based computing in managing distributed and intelligent systems. His research trajectory reveals a consistent focus on making complex, adaptive systems more intelligent, efficient, and practically deployable — work of growing relevance as automation continues to reshape industries worldwide.