Research interests

Advancing scalable platform architectures for reliability, automation, and operational excellence

My research agenda examines how scalable data platforms should be designed and governed, how AI agents can reconfigure the software development lifecycle, and how the token economics(tokenomics) of LLM-assisted software engineering can be improved for reliable, observable, and cost-efficient production use.

Scalable data platformsAI agents for software deliveryLLM token economics(tokenomics)Reliable AI engineering

Writing

Selected Articles

Agentic Data Unification (ADU): Building Trust in Autonomous Data Systems The Data City: A Practical Guide to Modern Data Engineering What Is Data Engineering? The Invisible Infrastructure of Modern Data Systems The Modern Data Stack - The Plumbing Beneath Your Data City Ingestion & Storage: How Data Enters the Data City

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Publications

Published Papers

Artifact Gate Evaluation for AI-assisted Software Delivery: A Controlled Study of Lifecycle Evidence

SSRN, 2026

Professional Service

Judge & Reviewer

Judge - Wave Hackathon 2026, ACM Seattle Chapter

Peer Reviewer - 10th IEEE Symposium on Wireless Technology & Applications (ISWTA 2026)

Peer Reviewer - IEEE International Conference on Industrial Technology & Computer Engineering (ICITCE 2026)

Engagements

Speaker

No speaking engagements are currently listed.

For collaboration on platform engineering, observability, enterprise data systems, or reliable AI, reach out on LinkedIn or by email.