Praveen Kumar GS

Praveen Kumar GS

Senior Director

Samsung R&D Institute

As the AI Leader and Senior Director of Engineering at Samsung Electronics, Praveen Kumar is responsible for creating a vision and strategy for AI in SRIB, especially in Generative and Agentic AI. He leads a group of over 200 talented AI engineers who are building the next-generation Assistant for Samsung AI Products with multimodal and conversational capabilities.

With over 23 years of extensive experience in strategic leadership, stakeholder management, delivery of customer-focused products, building talent and teams from scratch, and customer relationship management, Praveen has successfully handled many "Research to Market" projects under high-pressure conditions, utilizing agile methodologies and hybrid architectures. He has also developed and maintained a network of AI champions and established research collaborations with government agencies and top IITs in the areas of Artificial Intelligence. Praveen is passionate about transforming AI strategy into products that deliver new impact and user experience to the world.

As Artificial Intelligence matures from predictive systems to autonomous, goal-driven agents, the convergence of Agentic AI and Responsible AI becomes not just essential—but inevitable. This talk explores the dynamic intersection where the empowerment of intelligent agents meets the ethical guardrails of responsible design.

Agentic AI systems are capable of perception, decision-making, and autonomous action, often orchestrating complex tasks with minimal human oversight. While this unlocks immense potential—from personal assistants and self-optimizing systems to autonomous operations—it simultaneously introduces unprecedented challenges related to accountability, fairness, transparency, and control.

This power talk delves into:

  • What defines Agentic AI in the current technological landscape.
  • Core principles of Responsible AI and why they must evolve for agentic contexts.
  • Key friction points—such as autonomous goal misalignment, emergent behavior, and explainability gaps.
  • Real-world use cases and frameworks where agentic autonomy has been successfully aligned with responsible governance.
  • A forward-looking blueprint: design principles and policy anchors for building responsible agents that are trustworthy, aligned, and auditable.


By bridging agentic capabilities with ethical imperatives, this session aims to inspire technologists, leaders, and policymakers to co-create AI systems that are not only intelligent—but also accountable, safe, and deeply human-centered.

Read More

Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More

Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More