I engineer scalable communication apps and mobile experiences where reliability, performance, and user trust are non-negotiable.
Streamlined how users surface critical updates in high-volume environments, reducing cognitive load and helping teams spend less time searching and more time doing.
Modernizing core communication experiences by improving comprehension, workflows, and system consistency at scale.
Aegis-A11y is a hybrid AI framework for automating accessibility remediation of complex educational digital assets (e.g., STEM diagrams, multi-column layouts, nested tables, and scanned worksheets) that often fail under OCR-only or heuristic auto-tagging tools. The system follows a Decomposition–Reasoning–Reconstruction (DRR) pipeline: a computer-vision layout stage detects and classifies page regions, a multimodal LLM layer generates context-aware semantics (especially alt-text), and a deterministic verifier checks structural rules (e.g., heading order, table associations, and checklist-style WCAG screening) and triggers corrective loops when violations are found.
I am always looking to connect with engineers and researchers working at the intersection of AI, Accessibility, and Scalable Systems.