Selected for GSoC 2026 to build automated compilation verification across all 16 Concerto code generation targets (Java, TypeScript, Go, Rust, C#, GraphQL, Protobuf and more), closing a gap where CI only checked that the generator ran without crashing.
Architected per-target Docker images bundling the Concerto CLI and language toolchains, publishing to GitHub Container Registry with layer caching to keep CI builds fast.
Built a GitHub Actions matrix workflow that generates code from a versioned .cto test corpus and compiles/validates it inside the correct container on every pull request, failing fast on invalid output.
Co-developed the backend architecture of a Flask-React system, implementing secure authentication and role-based access, while building scalable APIs for core workflows and improving operational efficiency by 40%.
Outlined and implemented the full database architecture using SQLAlchemy ORM; deployed on a VPS with MySQL, SMTP, and production-grade rate-limiting and request validation.
Designed and trained 30+ deep learning model variants to classify oral and ear scan videos for a public health screening of 1M+ children.
Used MobileNetV2, ResNet and LSTM architectures to achieve 85%+ accuracy using data augmentation and cross-validation, while extending the work with minLSTM/minGRU for efficiency.