Publications
6
Current preprints and research manuscripts.

Principal Engineer, Independent Researcher
Designing scalable cloud-native systems and practical AI research pipelines for production use.
Exploring reliable LLM systems, cloud-native architecture, and production-ready AI research pipelines.
Publications
Current preprints and research manuscripts.
Open Source Libraries
Published and actively maintained on PyPI.
Featured Projects
Focused on LLM evaluation, tooling, and reliability.
Engineering Experience
Distributed cloud-native systems across enterprise domains.
Software engineer and researcher with 12+ years building large-scale cloud-native systems across enterprise domains. M.S. in Software Engineering (San Jose State University) with deep expertise in AWS microservices, Java, Python, Spring Boot, Docker, Terraform, CI/CD, and data-intensive platforms. Current research focuses on LLMs, RAG, LangChain, and explainable AI to bridge peer-reviewed innovation with production-ready intelligent systems.
Selected publications and preprints across LLM systems, RAG evaluation, and applied AI research.
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2010
CareerCompleted B.Tech. in Information Technology.
2010 - 2014
CareerWorked across enterprise software programs and core platform delivery.
2014 - 2016
CareerCompleted graduate studies focused on architecture and scalable systems.
2015 - 2016
CareerContributed to big data and platform engineering initiatives.
2016 - 2017
CareerFull-time role building data-intensive systems and production pipelines.
2017 - Present
CareerLeading cloud-native distributed systems and production engineering programs.
Peer Review
Issuer: Web of Science Academy
Online, California, US
View credentialResearcher Academy
Issuer: Elsevier BV (Netherlands)
Amsterdam, North Holland, NL
View credentialPeer Review
Issuer: Association for Computing Machinery
New York, New York, US
View credential2 stars
Zero-dependency empirical Big-O complexity checker for Python with CLI, assertions, and pytest integration
1 star
A comprehensive framework for evaluating evidence coverage and faithfulness in RAG systems
1 star
Official implementation of CoL-CE: A framework for evaluating reasoning validity in RAG systems
1 star
Experimental framework and empirical results demonstrating reasoning divergence, epistemic drift, and semantic skew using local LLMs (Ollama)
1 star
Implementation of Subspace Collisions in Knowledge Editing. Stable, scalable model editing with Orthogonal Low-Rank Updates
0 stars
A static performance linter that detects slow Pandas anti-patterns before they reach production
A snapshot of my core systems engineering, backend, DevOps, and AI/ML stack across real-world production and research workflows.
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