Dr. Swati Dhondiram Jadhav is an Assistant Professor in the Department of Electronics and Telecommunications Engineering at Ratan Tata Maharashtra State Skill University, Kharghar, Navi Mumbai, India. She also serves as a Postdoctoral Researcher at Multimedia University (MMU), Malaysia, working on AI-driven semiconductor device architectures for scalable quantum computing under the supervision of Assoc. Prof. Dr. Ooi Chee Pun. She holds a Ph.D. in Electronics and Communication Engineering from Chhatrapati Shivaji Maharaj University, Navi Mumbai (2025), an M.E. in Digital Communication from Dr. BAMU, Aurangabad (2014), and a B.Tech from S.G.G.S.I.E.&T, Nanded (2008). With over 14 years of teaching experience, she has taught a wide range of subjects including Data Science, Quantum Computing, Digital Signal Processing, and Full Stack Development. Her research interests span AI/ML engineering, cloud-native technologies, semiconductor device architectures, quantum computing, and cybersecurity. She has published extensively in IEEE and Scopus-indexed journals, holds multiple patents, and has authored a textbook and several book chapters. She has received research grants, the Research Excellence Award from Science Publishing House, and serves as a reviewer for numerous international conferences and journals. She is a member of IAENG, IRED, and SIPH, and has delivered keynote speeches and served as an expert resource person for various faculty development programs

Abstract Title: Bridging Intelligent Software Architecture, AI/ML Engineering, and Cloud-Native Technologies: A Practical Framework for Industry 5.0 Applications Abstract:The rapid convergence of Artificial Intelligence (AI), Machine Learning (ML), and cloud-native computing is transforming the design and deployment of intelligent software systems. Modern applications demand scalable architectures that can process real-time data, support autonomous decision-making, and adapt dynamically to changing environments. This keynote presents a practical framework for integrating intelligent software architecture with AI/ML engineering and cloud-native technologies to build resilient, secure, and future-ready applications. The presentation explores the evolution from monolithic systems to microservices, containerization with Docker, orchestration using Kubernetes, and cloud-based AI model deployment. It also demonstrates how data pipelines, RESTful APIs, and MLOps practices enable continuous development and intelligent service delivery. Real-world examples from smart manufacturing, healthcare, IoT, and Industry 5.0 illustrate the practical implementation of these technologies. The session aims to provide researchers, educators, and industry professionals with actionable strategies for designing interoperable and scalable intelligent systems while addressing challenges related to security, sustainability, and ethical AI. The proposed framework serves as a roadmap for bridging software architecture and AI-driven cloud ecosystems for the next generation of digital innovation. Keywords: Intelligent Software Architecture, Artificial Intelligence, Machine Learning, Cloud Computing, Microservices, Kubernetes, MLOps, Industry 5.0, IoT, Cloud-Native Technologies