I build data systems for environments where a single compromised credential can expose millions of patient records.
By day I'm a Senior Healthcare Data Engineer at Axle Informatics, designing zero-trust pipelines for genomic and clinical data at NIH scale. I also run Deterministic Systems Lab, where I do independent security research, and I'm a doctoral student in AI/ML at George Washington University.
Most of my work orbits a core problem: identity and trust in high-velocity data systems. I developed the Identity-Per-Transaction protocol — credentials that are cryptographically scoped to a single transaction and gone the moment it completes, published in IEEE BigDataSecurity. From there I've been building outward: cryptographic lineage so every transformation is auditable, and purpose-aware query governance using graph neural networks to enforce data use restrictions before a result ever leaves a clinical knowledge graph.
I spend a lot of time thinking about what 'secure by design' actually means when your data is regulated, your pipelines are serverless, and your threat model includes people who work there.
Happy to talk shop on any of it; find me after the talk or just grab me in the hallway.