Chirag Shah
Chirag Shah is an Environmental Data Science Engineer and full-stack software developer working with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility Data Center. His work focuses on building scalable scientific data systems that improve the discoverability, accessibility, and usability of large-scale atmospheric and environmental observations.
At the ARM Data Center, Chirag leads the design and development of modern research software platforms used by scientists to explore, analyze, and interact with complex observational datasets.
Chirag's technical interests span scientific data management, distributed systems, artificial intelligence, machine learning, and advanced data visualization. His work emphasizes building robust infrastructure and user-centric tools that enable researchers to efficiently work with large observational datasets and accelerate scientific discovery in Earth and environmental systems research.
Committed to advancing modern research software practices, Chirag actively explores emerging technologies that enhance the way scientists interact with complex data ecosystems.
Session
The Atmospheric Radiation Measurement (ARM) User Facility Data Center (ADC) capable of supporting scalable, secure, and reproducible engagement with atmospheric research data is evolving towards AI-ready ecosystem. We will discuss architectural designs utilized in production scientific data setting including open-source technologies to further multi-agent coordination, agentic retrieval-augmented generation (A-RAG), shared contextual memory via vector stores, and model-agnostic inference orchestration within Kubernetes infrastructure. We will go over ARM's foundational stack designed to support agentic AI workflows for data discovery, metadata research, reasoning, and user engagement. Additionally, we will go over architectural decisions, trade-offs, and security measures pertinent to research computing environments with some demonstrations.