Accelerated CS @ Boston University, graduating a year early. I build production systems as the sole engineer — a degree planner used by ~950 students, and a nonprofit's entire 250+ endpoint platform. Alongside that, I contribute to the LLM inference stack (vLLM, llm-d, KServe, InstructLab): my niche there is finding the paths a new feature quietly fails on.
CTO & Sole Engineer Honor Society of Cinematic Arts Multi-tenant platform · 250+ endpoint API · live across 15+ chapters & 150+ members portal |
SWE Intern BU Spark! Harvard Herbaria OCR confidence layer (FastAPI) · micro-credentialing platform · BU Spark!'s project showcase (sole author, live at atlas.buspark.io) |
SWE Intern Doro (Local Treasure) TikTok OAuth, Stripe checkout & moderation tooling (Django/DRF) getdoro.co |
Research Assistant BU CISS Financial markets × geopolitical uncertainty · Python data workflows |
Previously — AI & Software Engineer Intern @ HireBuddy · Lead Software Engineer @ Hack4Impact BU
I contribute to vLLM, llm-d (a CNCF sandbox distributed LLM inference stack founded by Red Hat, Google Cloud, IBM Research, CoreWeave and NVIDIA), KServe, Grafana, Redis, Keras, and Red Hat's InstructLab. Contributions now also span Grafana, Redis (node-redis — merged fix), Prisma, MLflow, Keras, Datadog, and the Model Context Protocol registry — same method everywhere: reproduce the failure with executed evidence before proposing the fix.
64 pull requests across 24 repositories in 17 organizations |
23 merged — including a fix in Grafana core shipping in 13.3.0, plus vLLM, node-redis, Keras and KServe |
9 defects found and filed against a newly released no-Kubernetes deployment path, 6 reproduced live with tracebacks |
~30 substantive code reviews and root-cause analyses on other contributors' PRs and issues |
What I am actually useful for: running a brand-new feature on a machine its maintainers do not have, a clean macOS laptop with no cluster and no GPU, and finding the paths where it reports success while doing nothing. That produced nine issues against one feature, including a container name collision that let one deployment's teardown destroy a sibling deployment's running containers.
Reviewing counts too. On someone else's pull request I found that a proposed dependency pin would fail the project's own version comparison, so every install would re-run the installer and silently overwrite the user's kubectl binary. Proven by running the project's own function against the proposed value.
Also opened fixes merged into the Kubernetes SIG's gateway-api-inference-extension (3 merged, 1 draft) and open PRs against SGLang.
|
Autonomous banks, central banks & payment rails (RTGS/ACH/SWIFT/CLS/DTCC), systemic-risk analysis, crisis replay & a hand-written regulatory DSL.
|
Degree planning for ~950 BU students across nearly 10,000 courses. Requirement-validation engine, vector-embedding semantic recommender replacing a quota-limited LLM at zero marginal cost, Redis layer at ~81% hit rate over 660k+ lookups.
|
|
The production system of record behind my CTO role — member lifecycle, payment-gated resources, evaluation forms & a film festival, with per-chapter tenant isolation.
|
Built the AI candidate-sourcing engine (Elasticsearch-DSL over CoreSignal) — tripled candidates surfaced per search (100 → 300) — and co-built a GPT-4o-mini pre-screening engine scoring across 10 evidence-backed dimensions.
|
OCR confidence-preservation layer for a specimen-digitization ML platform — a versioned per-field certainty envelope surfacing Azure vision-OCR to reviewers, plus SSRF + authorization hardening. Client-owned (BU Spark!) — no public repo |
Owned the SE-Chem badge-authoring wizard end-to-end — decomposed an 843-line page into components, killed a stale-closure bug, and batched Client-owned (BU Spark!) — no public repo |
🏆 InstructLab KnowFlow LangGraph + MCP agentic workflow automating InstructLab contributions — accepted for upstream evaluation. |
🥈 Cognify AI course & career advisor over 6,000+ BU courses with Gemini recommendations & skill-gap analysis. |
⚛️ Quantum Explorer Interactive 3D quantum-entanglement platform with AI-powered concept grading. |
%%{init: {'theme':'base','themeVariables':{'primaryColor':'#171F33','primaryTextColor':'#E6EDF3','primaryBorderColor':'#14B8A6','lineColor':'#10B981','fontSize':'14px'}}}%%
flowchart LR
UI["Frontend\nReact · Next.js · Three.js"] --> API["APIs\nFastAPI · Flask · Express · DRF"]
API --> AI["AI Layer\nLangGraph · MCP · embeddings · TF-IDF retrieval"]
API --> DATA[("Data\nPostgres · Redis · Elasticsearch")]
AI --> DATA
API --> INFRA["Infra\nDocker · AWS · Vercel · Railway"]
DATA --> INFRA
