Swapneswar Sundar Ray is an AI and software engineering leader with extensive experience designing and scaling enterprise artificial intelligence, generative AI, agentic systems, cloud platforms, and intelligent automation solutions. He currently serves as an Assistant Vice President in AI Systems Engineering and Principal Machine Learning Engineer, where his work focuses on building reliable, governed, and production-ready AI systems for complex enterprise environments.

Ray is an active contributor to the global AI and technology community. He has evaluated more than 100 projects and innovation submissions through international technology competitions and has served as a peer reviewer for numerous conferences, including IEEE-affiliated events. He also serves on editorial boards and conference program committees, contributing to the evaluation and advancement of emerging research in artificial intelligence, data science, intelligent systems, and software engineering.

He is the author of two technical books on artificial intelligence and generative AI and has published more than 20 articles on AI, agentic systems, cloud-native architecture, platform engineering, AI governance, and enterprise technology. His research portfolio includes multiple accepted conference papers and ongoing journal research focused on trustworthy AI, autonomous systems, AI governance, enterprise architecture, and resilient intelligent platforms.

His professional and scholarly contributions have earned industry recognition, including selection for the AI150 Awards 2026. Combining hands-on engineering leadership with research, publishing, reviewing, and judging experience, Ray brings a practical and multidisciplinary perspective to evaluating innovation—looking not only at technical novelty, but also at real-world impact, scalability, responsible AI practices, feasibility, and long-term value.

As a judge for Reimagine2026, he brings deep expertise in assessing AI-driven solutions and identifying ideas that demonstrate meaningful innovation, strong engineering foundations, responsible implementation, and the potential to create measurable real-world impact.