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Chitral Patil

Proof of work

Projects

Not a GitHub dump — a few things that show how I think. The flagship is the meter; the rest trace the same instinct backward.

Flagship · open source

vllm-cost-meter

Objective live telemetry + effective cost-per-million-token meter for vLLM servers.

A read-only observer for running vLLM servers that ingests Prometheus metrics and surfaces live effective LLM serving cost against the operator's actual traffic.

  • Reads vLLM Prometheus metrics
  • Tracks throughput, request rate, TTFT, TPOT, E2E latency, prompt / generation lengths, batch state, and KV cache
  • Computes live effective cost-per-million-token visibility
  • Ships benchmark reference curves from the paper
  • Independent, reproducible research artifact

AI infrastructure

Data, finance & SEC research

SEC EDGAR / 10-K ETL

source on request

Pipelines that scrape and structure financial filings for accounting and fraud-signal research.

What it shows — Comfort with messy real-world data and the patience to model it properly.

University at Buffalo faculty scraper

source on request

Data-extraction tool that collected and normalized faculty information at scale.

What it shows — Early proof of the same habit: automate the boring extraction, keep the signal.

Product experiments

Propael

source on request

Job-application tooling — ATS-friendly cover letters and application workflow.

What it shows — Product sense: build the thing people actually need, ship it, learn.

Reinforcement learning web app

source on request

Interactive app for exploring and teaching RL concepts in the browser.

What it shows — Teaching instinct — understanding something well enough to make it playable.

Creative tools

TextExtend-AI

source on request

AI-assisted document and text tooling experiment.

What it shows — Curiosity about where language models help real writing work.

More on GitHub

Older projects are framed as curiosity and shipping, not headline claims.