Cloud Infrastructure · AI Systems · Capacity Strategy
Researcher and practitioner defining how hyperscale cloud systems are built, scaled, and made resilient — from exabyte-scale storage to AI supercomputing infrastructure.
I am a cloud infrastructure strategist and researcher with 12 years defining how hyperscale systems are built, scaled, and sustained. My work spans the full lifecycle of large-scale infrastructure: from capacity planning and architecture strategy to multi-region data center launches and next-generation storage platform design.
My career has been deliberately cross-domain. I began as a physical network engineer, moved through business intelligence and machine learning, and arrived at senior infrastructure leadership through deep, hands-on technical fluency across every layer of the stack. This breadth gives me a rare ability to operate where engineering rigor meets program complexity — and to translate both into research and industry discourse.
My research focuses on compute-disaggregated storage architecture, AI infrastructure demands, supply chain-constrained scaling, and the capacity planning frameworks that govern multi-billion-dollar infrastructure investment decisions. I write and speak as an independent practitioner, bringing first-hand experience at a scale few researchers can claim.
Deep expertise in compute-disaggregated storage design, QLC/TLC NAND economics, Heat Assisted Magnetic Recording (HAMR) adoption, and the TCO frameworks that govern storage decisions at exabyte scale. Research focus on the transition from monolithic to disaggregated infrastructure models.
Defining capacity forecasting models, hardware procurement governance, and rack-level topology optimization for AI/ML training and inference workloads. Applied understanding of how GPU-accelerated compute clusters impose storage and networking requirements that reshape infrastructure strategy.
Authoring multi-year infrastructure investment roadmaps and CapEx governance frameworks for systems at planetary scale. Translating demand signals into procurement decisions — balancing supply chain risk, technology adoption timing, and cost optimization across long planning horizons.
Research-grade analysis of latency, cost, and resilience trade-offs in multi-region deployments. Applied experience coordinating data center fit-out — power, cooling, rack placement, network topology — across commercial, GovCloud, and international sovereign environments.
Driving the strategic decision to invest in near-zero-touch infrastructure automation — defining architecture, securing cross-organizational buy-in, and delivering measurable reduction in manual operational effort. Applying AI tools to accelerate program execution and workflow automation at scale.
Designing end-to-end data pipeline architectures for fleet health monitoring and capacity observability. Building the unified telemetry platforms that shift infrastructure teams from reactive data gathering to proactive, insight-driven decision-making at executive level.
Featured in Science Times — a practitioner's perspective on planetary-scale cloud architecture, covering legacy system vulnerabilities, hardware-software co-design, AI workload demands, sovereign cloud isolation, and the program management discipline required to orchestrate large-scale infrastructure deployments.
Research examining how hyperscale cloud providers engineer resilient expansion programs when semiconductor and hardware supply chains impose binding limitations. Submitted to Springer Journal of Cloud Computing.
Practitioner-focused analysis of the architectural decisions governing multi-region deployments, with frameworks for evaluating latency requirements, data egress economics, and operational overhead. Submitted to InfoQ.
Industry commentary on compute-disaggregated storage models, supply chain-constrained scaling, and the infrastructure economics of serving AI/ML workloads at hyperscale. Submitted to The New Stack.
Presented at NIECE 2013, National Conference on Innovations in Electronics & Communication Engineering. Technically sponsored by IEEE MTT-S (India Council).
Presented at AREST '13, National Conference on Advances & Research in Electrical System Technology. Sponsored by IET-UK & ISTE.
Exabytes of compute-disaggregated storage infrastructure, globally distributed
Data center region launches across commercial, GovCloud & international environments
Reduction in manual launch effort through near-zero-touch automation
Active publications across peer-reviewed journals and industry outlets
Single-threaded owner of cross-functional infrastructure programs spanning storage platform architecture, capacity strategy, region launches, and zero-touch automation. Leading cross-organizational alignment across 120+ engineering teams. Influencing engineering roadmaps and infrastructure investment direction at VP/SVP level.
Architected the enterprise-wide decision-support platform for a large-scale COVID-19 testing program. Built a community infection rate benchmarking framework integrating county, state, and federal public health data — mapped to facility catchment areas weighted by commute patterns. Improved ML forecasting accuracy from 11% to 63%. Delivered recommendations to senior executive leadership, translating epidemiological data into operational procurement and resource allocation decisions with explicit uncertainty framing.
Identified systemic policy gaps that no one had previously surfaced — authored data-driven analysis that changed global enforcement policy across multiple regions, improving accuracy and reducing incorrect outcomes. Defined automation strategy for 18 ETL/ELT reporting pipelines, improving query runtimes by 83%.
Trusted technical advisor for mission-critical cloud architectures at platforms serving hundreds of millions of end users. Designed resilient multi-AZ architectures and managed complex distributed systems failures — building the cloud-native foundation underpinning current hyperscale infrastructure strategy.
Cross-functional network capacity planning and architecture for large-scale enterprise environments. BGP/OSPF/EIGRP design, vendor SLA governance, and production reliability standards — the first-principles infrastructure foundation everything else is built on.
Elected to IEEE Senior Member grade — the highest grade for which a member may apply directly, conferred upon fewer than 10% of IEEE's global membership. Recognized for sustained technical contributions and demonstrated engineering significance over a decade of professional practice.
✦ Conferred 2026Selected as a biographical listee in Marquis Who's Who in America — the flagship edition of the most prestigious biographical registry in the United States, published continuously since 1899. Inclusion is by invitation only, based on independent evaluation of professional achievement and recognition by peers across one's field.
✦ Invite-Based · Listee 2026Member of Women in Engineering — a global community advancing the participation, development, and recognition of women in engineering and technology. Contributing to a discipline-wide effort to expand representation at the senior leadership and research levels of cloud infrastructure and computing.
✦ MemberPursuing peer review contributions to IEEE Transactions on Cloud Computing and other tier-1 venues, alongside technical judging opportunities across industry and academic programs recognizing innovation in cloud infrastructure and distributed systems.
OngoingBuilding the infrastructure that powers the cloud — and looking to connect with researchers, editors, and practitioners working at the frontier of what's possible.
Open to peer review collaboration, speaking engagements, editorial contributions, and research partnerships in cloud infrastructure, AI systems, and capacity strategy.