I have contributed to a range of open‑source, research, and mentorship projects from 2019 to 2022, spanning observability, testing, cloud‑native tooling, information management, evolutionary optimization, and real‑time computer‑vision applications.
I worked on Thanos, adding features, context & actions to increase observability & control for BlockViewer.
I contributed to the Kubernetes client, extending support to 13 resource types and adding test coverage for 9 resources, while upgrading the test suite from JUnit4 to JUnit5.
I authored a real‑time ASL translator that achieved 95% accuracy.
- Jest – built a fast, low‑config JavaScript testing framework (June 2020‑present).
These projects shaped my approach to building observable systems, automating developer workflows, and deploying ML models at scale.
I presented the recommendation‑system research at the International Conference on Machine Learning, Computer Systems, and Security on May 21 2022.
- Quarkus (GSoC mentor) – improved Gradle support for Quarkus (Mar 2020‑present).
- Bundly – centralised MLH Fellowship information and auto‑generated markdown stand‑up notes (Jul 2020).
- Genetic Algorithm for COVID‑19 Vaccine Imaging – used evolutionary optimization to tune dropout rates for pneumonia detection (Jul 2020).
- Quarantime – built a GraphQL‑MongoDB social platform during the MLH Fellowship Orientation Hackathon (Jun 2020).