Speaker

Kumuda Sreenivasa

Kumuda Sreenivasa

Sr Data Architect ,ATC Drivetrain Founder ,Unimonk & GoIcure

New York City, New York, United States

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I am a Senior Data Architect at ATC Drivetrain and the Founder of two ventures—Unimonk, an AI-powered education platform, and GoICure, a digital-first medical tourism solution. I’ve spoken at KCD Washington 2025 and will also be presenting at BazelCon, sharing my experiences in cloud-native engineering and secure data systems. At ATC Drivetrain, I design hybrid cloud architectures that integrate AWS, Azure, Kubernetes, and big data pipelines for mission-critical shopfloor operations, driving improvements in governance, scalability, and predictive maintenance. Through GoICure, I’m building intelligent, compliance-ready platforms for cross-border healthcare, while Unimonk is focused on transforming education and university admissions through automation and AI. With a Master’s in Data Science from the University of Texas at Dallas and a strong foundation in distributed systems, MLOps, and secure data engineering, I bring both enterprise experience and entrepreneurial innovation to solving real-world problems at scale.

Area of Expertise

  • Health & Medical
  • Information & Communications Technology

Topics

  • Ai
  • Information Tehnology
  • Cloud Containers and Infrastructure
  • Database
  • Data Science
  • Healthcare AI
  • Healthcare Technology
  • AI in Health
  • AI
  • innovation in healthcare
  • Data Privacy
  • Microsoft Data Platform
  • Data Platform
  • Data Analytics
  • Data Governance

Immutable Infrastructure for Clinical AI: Bazel for Dependency Governance in Healthcare ML

Deploying AI in healthcare requires more than accurate models—it demands strict reproducibility, traceability, and compliance. In this talk, we explore how Bazel enabled a fully reproducible, audit-ready ML pipeline used in clinical radiology. We demonstrate how Bazel was used to manage Python, C++, and Docker-based components, enforce hermetic builds, lock dependencies, and generate Software Bills of Materials (SBOMs) for compliance. With Bazel, we achieved deterministic model training, sandboxed preprocessing, and secure inference packaging across multiple hospital environments. Attendees will gain insights into structuring Bazel for regulated machine learning workflows, managing multi-language codebases, and building trust in sensitive AI systems. This session offers practical strategies for engineering reproducible, scalable infrastructure in real-world clinical settings.

Kumuda Sreenivasa

Sr Data Architect ,ATC Drivetrain Founder ,Unimonk & GoIcure

New York City, New York, United States

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