Dr. Raj Sinha is an accomplished academician, researcher, and Assistant Professor in the Faculty of IT & Computer Science at Parul University. She holds a Ph.D. in Computer Science and is currently pursuing Post-Doctoral research in Canada. Her research interests include Artificial Intelligence, Machine Learning, Cyber Security, Data Science, and Digital Marketing. She has authored numerous Scopus-indexed publications, book chapters, patents, and conference papers, and has served as a keynote speaker, session chair, reviewer, and research mentor at several international conferences. Dr. Sinha is a Gold Medalist in Ph.D. (Computer Science) and has received multiple awards for excellence in research, innovation, and academic leadership.

Neuro-Symbolic Hybrid ML-DL Framework for Autonomous Cloud-Native Decision Intelligence The increasing complexity of intelligent digital ecosystems requires next-generation systems capable of reasoning, learning, adaptation, and autonomous decision-making. This paper proposes a Neuro-Symbolic Hybrid Machine Learning and Deep Learning (ML-DL) framework for autonomous cloud-native decision intelligence. The proposed architecture combines symbolic AI reasoning with deep neural learning models, including Transformer Networks, Graph Neural Networks (GNN), and Reinforcement Learning (RL), to enable explainable and adaptive intelligent systems. Cloud-native microservices and edge-cloud orchestration support scalable deployment and real-time distributed analytics. The framework is designed to support autonomous decision environments in smart cities, healthcare, finance, and cybersecurity applications. Experimental analysis demonstrates improved explainability, decision accuracy, scalability, and adaptability compared to conventional AI-driven architectures. The proposed system contributes toward the development of trustworthy and self-evolving intelligent digital ecosystems for future computing environments.