Sixteen years modeling natural and engineered hazards for the global (re)insurance market — building the geospatial decision systems capital gets allocated against. Founder of GeoRisk and CataclysmGuide; NASA grant peer reviewer; longstanding research interest in decision support for crewed planetary operations.
The common thread across 20 years of work is one methodological commitment: quantifying low-probability, high-consequence outcomes on portfolios of assets and lives under uncertainty. In reinsurance, that means EP curves and stochastic loss models. In grid resilience, it means black-sky scenario quantification. In cyber risk, it means systemic loss aggregation. In space systems, it means mission risk assessment and crew decision support under communications latency. The mathematics is agnostic to the application domain — and that gives me depth and breadth in my work. — Probabilistic Risk Engineering · A Multi-Domain Practice
Sixteen years of production probabilistic risk work across the senior tier of the global market — the same methods NASA formalises as Probabilistic Risk Assessment (PRA) under NASA/SP-2011-3421. The same mathematics DOD uses for installation resilience. The same frameworks DOE applies to grid hardening. The domain changes. The core methodology doesn't.
Tropical cyclone, severe convective storm, flood, wildfire, and earthquake modeling at portfolio scale. Sixteen years of production work across the senior tier of the global market — world's largest publicly traded P&C insurer, top-5 global reinsurer, and industry-leading CAT modeling vendors. The EP curve methodology underpinning CAT modeling is functionally equivalent to the Probabilistic Risk Assessment framework in NASA/SP-2011-3421 — scenario development, initiating event quantification, uncertainty analysis, and decision support across system life-cycle phases.
Live NOAA event ingestion, geospatial overlay against arbitrary asset portfolios, automated exposure quantification. GeoRisk is the operational reference architecture; applicable to installation resilience, energy grid hardening, and tactical situational awareness under DOE, DHS, and DOD authorities.
Catastrophe-style modeling of US power-grid exposure to high-consequence threat scenarios — Fortran simulation engine paired with a modern map-based UI for decision support. Developed in collaboration with InfraGard (including the National Disaster Resilience Center) and the Foundation for Infrastructure Resilience. Aligned with DOE CESER, EPRI, and national-laboratory grid-security programs.
Led the workstream on Operational Cyber Risk for the Institute and Faculty of Actuaries (IFoA) in 2020, authoring a cyber catastrophe modeling framework for the UK actuarial profession. Direct relevance to CISA, DHS, and DOD cyber resilience programs that increasingly use catastrophe-modeling methodologies for systemic cyber risk.
Longstanding research interest in decision systems for Mars and lunar surface crews — risk management at distances where Earth-loop communication is infeasible. Builds on prior NASA Constellation-era ISRU work (MIT TLO Case 19973). A research interest available to be activated through the right programme; not a current funded line.
MATLAB-based simulator for Martian ISRU, developed during a 2005 MIT internship on the NASA Constellation CER programme under the Presidential Vision for Space Exploration. Multi-contractor effort spanning MIT, Lockheed, Paragon, and other defense partners. MIT TLO Case No. 19973, IP rights formally released October 2017.
End-to-end design and build of GeoRisk: ingestion pipelines, spatial joins at scale, web rendering, underwriter-grade UX. Demonstrated capability to ship deployable systems, not prototypes — the differentiator most SBIR Phase II reviewers explicitly look for.
Active research extending undergraduate spinor / minimal-surface results toward Dirac-equation formulations. Foundational mathematics with applications in geometric mechanics, gauge theory, and theoretical propulsion physics relevant to AFRL and DARPA basic-research portfolios.
Active NASA grant peer reviewer since 2017 (specific programme under NDA). Working knowledge of federal review criteria, mission-directorate priorities, and the proposal evaluation rubrics applied — useful as PI from inside the review process.
GeoRisk overlays live NOAA hazard streams against user-uploaded asset portfolios in seconds. Built for (re)insurance underwriters; architected for direct extension into installation resilience, energy infrastructure, and supply-chain risk.
Live hazard exposure quantification — civilian product, dual-use architecture, asset-agnostic engine.
Continuous pull from authoritative hazard feeds — tropical, severe, flood, fire, marine — with provenance preserved end-to-end.
User uploads TIV portfolio (CSV, Excel); system performs geospatial intersection against active hazard polygons in seconds.
Automated TIV-at-risk calculation with breakdown by hazard type, severity, and confidence — underwriter-grade output formats.
The engine doesn't know it's for insurance. The same architecture runs against installations, grid assets, supply nodes, or any other portfolio of geolocated assets exposed to natural hazards.
Foundational mathematics, applied catastrophe research across natural and cyber hazards, and a longstanding interest in decision support for crewed planetary operations.
Real-time NOAA hazard intelligence platform for the (re)insurance market. Live ingestion of tropical, severe, flood, and fire feeds; spatial intersection against uploaded TIV portfolios; underwriter-grade exposure reports. Pre-launch.
GenAI-powered catastrophe modeling assistant — the future of exposure management and CAT decision support. Built on large language model foundations tuned for the (re)insurance and risk engineering domain.
Extending undergraduate result that H = 0 iff the ratio of spinor components is anti-holomorphic, toward the matching of geometric Dirac structure to its physical counterpart.
Established direct correspondence between minimal-surface condition and spinor-component anti-holomorphy. Supervised by Drs. Grantcharov and Draghici, supported through the McNair fellowship. Origin of the present research line.
Led the workstream on Operational Cyber Risk for the Institute and Faculty of Actuaries (IFoA), authoring a cyber catastrophe modeling framework for the UK actuarial profession. Presented at IFoA conferences and circulated as a profession-level reference.
Developed during a 2005 MIT internship on the NASA Constellation CER programme under the Presidential Vision for Space Exploration. Multi-contractor effort across MIT, Lockheed, Paragon, and other defense partners. MIT TLO Case No. 19973, IP rights formally released October 2017. Code base available for review.
A long record of contributing to the public technical commons — from foundational mathematics texts to operating systems education, and two archive sites documenting hardware engineering and systems work going back to 2008.
Listed contributor to the open-source Abstract Algebra Wikibook — groups, rings, fields, modules. Open mathematics text, used as a free reference by students globally.
Named in the contributions and thanks of OSTEP, the canonical open operating systems textbook, latest online edition.
Early engineering portfolio documenting 3D terrain visualization, RF/WiFi projects, Tesla turbine designs, real-time weather data systems, and interactive GIS — the hardware and systems track that predates the CAT-modeling career.
Graduate-era build log documenting the FTIR multi-touch table project (NIR webcam modification, acrylic surface fabrication, IR LED arrays), Orion capsule encounter at the NASA TweetUp, and the Constellation CER reference — the earliest public technical record, 2008–2011.
Available for SBIR/STTR partnerships, OTA engagements, direct federal contracts, and consulting on catastrophe modeling, geospatial decision systems, and critical infrastructure risk. SAM.gov registered, NASA grant peer reviewer, InfraGard member.