I'm Hongchen (Steven) Yang, a computer science student at Brandeis University. I study adaptive storage systems and build AI agent workflows.
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Lazy pipelines for Python iterables and records, with bounded async concurrency and native execution paths.
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See Git changes on individual lines inside VS Code's native notebook editor, including edits you haven't saved yet.
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Dependency audits grounded in declarations, lockfiles, and source usage. Shared by a CLI, MCP server, and agent skill.
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Football data, match analysis, and model comparisons that keep training and evaluation periods separate.
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My research focuses on FluidLSM and RocksDB tuning for changing workloads. I study how access patterns affect compaction and performance in LSM trees. I build controlled benchmarks to evaluate adaptive tuning methods.