Obed Boateng
Papers
3
Total Citations
24
H-Index
3
About
Obed Boateng is an emerging researcher at the forefront of intelligent automation and artificial intelligence-driven process optimization. His work sits at the critical intersection of Robotic Process Automation (RPA), machine learning, and deep learning, addressing one of modern enterprise technology's most pressing challenges: moving beyond rule-based automation toward genuinely adaptive, predictive systems. Boateng's most notable contribution examines the integration of machine learning models with UiPath for predictive analytics and end-to-end decision automation, a paper that has already accumulated 14 citations since its 2025 publication — a remarkable early impact. His research extends this vision further through investigations into Microsoft Power Automate embedded with deep learning algorithms for real-time process adaptation, as well as pioneering work applying reinforcement learning techniques to cognitive automation within platforms like UiPath and Automation Anywhere. Collectively, his publications have garnered 24 citations within a single year, signaling strong and growing interest from the automation research community. Boateng's scholarship is particularly valuable for practitioners and academics seeking to understand how next-generation AI techniques can transcend the limitations of conventional RPA, enabling intelligent systems capable of dynamic learning, autonomous decision-making, and continuous process improvement across complex organizational environments.
Research Focus
Key Achievements
Top Papers
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