keynote & Distinguished Speakers FOR CISS2026 & SSRAAI2026

NIRMAL JINGAR

Job Title: Sr. Engineering Manager

Affiliation: Wayfair

LinkedIn Profile: https://www.linkedin.com/in/nirmaljingar/

From AI Systems to Governed Intelligence: Building Deterministic, Auditable AI for Society

Abstract: Artificial intelligence is rapidly becoming a core decision layer across institutions, yet most systems remain opaque, probabilistic, and difficult to govern. This keynote introduces a shift from conventional AI systems toward governed intelligence, in which outputs are not only generated but also validated, constrained, and held accountable before use. It explores how deterministic frameworks, auditability, and policy-driven controls can transform AI from a tool of experimentation into a system of record that organizations and society can rely on.

Drawing on real-world applications in enterprise and governance contexts, the session examines how boards, executives, and technology leaders can rethink risk, compliance, and trust in AI adoption. It also highlights the importance of designing AI systems that are explainable, reproducible, and aligned with regulatory expectations. The goal is to move beyond innovation for its own sake and toward AI that is dependable, transparent, and fit for critical decision-making at scale.

Dr. (Mrs.) Bhavna Mahadew

LL.B.(Hons); LL.M; LL.D. ( University of the Western Cape)

Lecturer in Law 

Department of Business Management and Law; 

School of Business, Management and Finance; 

University of Technology, Mauritius, 

Deputy Editor-in-Chief - African Journal of Law and Justice System ( SCOPUS INDEXED)   

Adjunct Professor ( CSIBER INDIA) 

Reimagining the Social Sciences in the Age of Artificial Intelligence: Ethics, Governance, Human Agency, and Global Transformation. 

Abstract: The rapid evolution of artificial intelligence is reshaping not only economies and technologies, but also the very foundations of human society, governance, and knowledge production. This keynote address explores how AI is transforming the social sciences by redefining the ways researchers investigate human behavior, public policy, education, culture, development, and institutional governance. Drawing on interdisciplinary perspectives, the address examines the opportunities created by AI-driven methodologies, big data analytics, and intelligent systems in generating new forms of social insight and evidence-based decision-making. At the same time, the keynote critically reflects on the ethical, legal, and societal implications of the increasing integration of AI into social life. Particular attention will be paid to issues of human rights, algorithmic governance, digital inequality, privacy, bias, accountability, and the future of democratic participation in technologically mediated societies. The address will also consider how AI can contribute to sustainable development and global resilience while avoiding the reproduction of existing structural inequalities. By bringing together themes of human-AI interaction, computational social science, policy innovation, and global development, the keynote argues that the future of social sciences lies not in replacing human inquiry with machines, but in developing responsible, inclusive, and human-centered AI ecosystems that enhance our collective capacity to understand and improve society. The presentation ultimately calls for a renewed partnership between technology and the social sciences to ensure that the AI revolution remains anchored in ethics, justice, and human dignity.

Bhanu Sekhar Guttikonda

Senior Software Engineer, Capital One, USA

Areas of Expertise: Full-Stack TypeScript Engineering, Cloud & DevOps Architecture, AI-Driven Systems, API Platforms, and Large-Scale FinTech Integrations

LinkedIn: https://www.linkedin.com/in/bhanusekharguttikonda/

Integrating CI/CD Pipelines for AI with Low-Code Development: Scalable, Reproducible, and Industrial-Ready AI Systems

Abstract: Modern AI-driven applications require deployment frameworks that are scalable, reproducible, and efficient, especially in industrial environments where reliability and real-time processing are essential. This keynote presents a unified framework that integrates CI/CD pipelines with low-code development to enable seamless AI model training, deployment, monitoring, and continuous retraining. Drawing on experiments using NEU Surface Defect, CIFAR-10, and Intel Image Classification datasets, the talk illustrates how ResNet18-based models can be operationalized using Jenkins, Docker, Kubernetes, and ArgoCD to achieve enterprise-grade automation. The framework promotes accessibility for non-technical domain experts through low-code interfaces, reduces operational overhead, and ensures consistent model performance across environments. By combining deep learning, GitOps-driven CI/CD automation, and containerized deployment, this approach bridges the gap between AI research and real-world industrial adoption. Attendees will gain a practical understanding of how to build AI systems that are scalable, continuously improvable, and production-ready.

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