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Speaker

Krishnendu Dasgupta

Krishnendu Dasgupta

Founder, AXONVERTEX AI

Bengaluru, India

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Krishnendu Dasgupta is an engineer with 15+ years in applied Machine Learning . His interests span across healthcare, generative AI, and decentralized AI. He is currently applying AI innovation in clinical trials, graph ML, NLP, and privacy-preserving AI. A Stanford Code in Place mentor and MIT Bootcamp alum, he’s contributed to NIST, MIT Hacking Medicine, and won the Molypix AI award (MIT, 2025). Krishnendu focuses on ethical, scalable AI with global impact. He spoke at The Linux Foundation AI Dev Summit in 2025, and recently at NODES 2025.He has contributed to more than 12 books published globally on Artificial Intelligence and Machine Learning, published by Springer Nature.

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Area of Expertise

  • Health & Medical
  • Information & Communications Technology

Topics

  • Artificial Intelligence
  • Generative AI
  • AI Agents
  • Compilers
  • AI Policy
  • Healthcare AI

Privacy as Infrastructure: Declarative Data Protection for AI on Kubernetes

AI services are multiplying faster than privacy controls can keep up. This talk covers a Kubernetes-native approach to make privacy "just work": an open-source framework that treats data protection as infrastructure, not application code. It introduces the concept of a Privacy Operator that discovers AI and ML workloads, applies declarative privacy policies, and enforces anonymization at deployment and runtime. Instead of developers wiring in libraries or filters, the platform ensures that sensitive data never leaves a workload unprotected. We will demonstrate the architecture, policy model, and enforcement patterns, from webhook-based mutation to service-level mediation, with key trade-offs for latency, reliability, and observability. This session will show privacy automation in action as policies update dynamically across running AI workloads.

AGENTS OF S.E.A.L.E.D: AI Agentic Cybersecurity Framework


The Agents of S.E.A.L.E.D (Secure, Encrypt, Analyze, Locate, Eliminate, Defend) framework introduces an agentic ecosystem for cybersecurity structure leveraging AI-driven cryptography and intelligent agent-based guardrails. Our research focuses on deploying customizable AI agents that integrate encryption, real-time threat analysis, cyber threat localization, targeted elimination, and robust defense tactics.

This session explores practical and foundational approaches using frameworks like Semantic Kernel and AutoGen, along with guardrails models such as IBM Granite and Meta Llama Guard. Attendees will learn about RAG, RAF, Graph-RAG, and RHLF methodologies for cybersecurity, with attention to compliance (Digital Protection Act, US/UK Privacy Acts).

The session will highlight agent-to-agent communication,decentralised framework , and multimodal data integration (text, voice, image, video) to transform cybersecurity strategies. Discussion includes plug-and-play deployment, agent orchestration, and real-time policy-to-action pipelines.

Disclaimer: Research-oriented implementations only.

NODES 2025 Sessionize Event

November 2025

AI_dev: Open Source GenAI & ML Summit Europe 2025 Sessionize Event

August 2025 Amsterdam, The Netherlands

Krishnendu Dasgupta

Founder, AXONVERTEX AI

Bengaluru, India

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