Matthew Marshall

• Architect and principal author of aion (~6,200 of 6,450 commits), a declarative, multi-tenant application platform where AI agents are first-class participants under machine-checked contracts, together with the build and deploy substrate it runs on.6,200 commits
• Mechanized the normative specification in Lean 4: a 57-RFC suite reduced to a seven-proposition kernel, with 1,400+ machine-checked theorems across 570 modules covering permission algebra, bitemporal CRDT convergence, safe schema migration, and typed-expression soundness. Proofs run as Bazel test targets, so a spec regression fails CI like any other test.1,400+ proofs
• Stood up a self-hosted Buildbarn remote-execution and cache plane: cold clone to built in 175 s (vs. ~48-min GitHub Actions baseline), two bzlmod registries serving 100+ rules_* modules behind machine-checked conformance gates, blast-radius-scoped test selection as the merge gate, and SOC 2 evidence emitted as a control-plane byproduct.175 s

• Led the development of a microservices-based portfolio benchmarking engine using gRPC and Protobuf, supporting arbitrarily complex composite index calculations, real-time FX conversion, and flexible fund performance comparisons.

• Directed NSF-funded R&D as PI for two grants (1722276 and 1927042) focused on using symbolic AI and optimization to address climate-based financial risk management. Managed personnel, budgets, timelines, and reporting requirements.2 grants
• Optimized geospatial clustering algorithm for reinsurance customer, significantly reducing O(n2) runtime complexity for distance matrix calculations by using H3 as a discrete global grid system and parallelizing with TensorFlow.O(n²)

Undergraduate research culminated with the development of a mobile app for creating labeled reinforcement learning datasets for wearable sensor data. The app let the user adjust the position of a stylized stick figure so that the activity sensor data could be properly classified. This project preceded the mobile era and was written for Windows CE using several custom graphics libraries and toolkits. Activities: MIT Football, Lambda Chi Alpha.