A. Kakoli Rao
Papers
1
Total Citations
17
H-Index
1
About
Dr. A. Kakoli Rao is a distinguished researcher at the intersection of software engineering, machine learning, and defense automation. Her most-cited work, "Software Reliability Analysis with Various Metrics using Ensembling Machine Learning Approach" (2023, 17 citations), pioneers the use of ensemble learning techniques to predict and enhance software dependability—a critical contribution as systems grow increasingly complex. Beyond reliability, Dr. Rao’s research extends to autonomous surveillance, where she has proposed integrating robotic systems into military security frameworks to monitor international borders with minimal human intervention. Her work addresses the urgent need for robust, intelligent monitoring in high-stakes environments, combining predictive analytics with real-time automation. With a growing citation footprint, Dr. Rao’s contributions are shaping the future of both software quality assurance and defense technology. Her innovative approach to ensembling methods offers practical solutions for ensuring system resilience, while her vision for robotic border patrol highlights a commitment to applying machine learning for national security. For students and researchers, Dr. Rao’s work exemplifies how computational methods can solve pressing real-world challenges, from code reliability to autonomous defense.
Research Focus
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Top Papers
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