Projects
Research and engineering work in LLMs, NLP, and AI agents.
Open-Source Python Package
ragbenchpy — RAG Pipeline Benchmarking
- Published to PyPI a benchmarking tool that runs every chunker × retriever combination for a RAG pipeline and reports accuracy (recall, precision, hit rate, MRR, nDCG), latency (p50/p95/p99), and cost per query side-by-side.
- Supports fully local evaluation via Ollama and Hugging Face or bring-your-own OpenAI/Anthropic/Google keys, auto-generates benchmarks from unlabeled documents using an LLM, and isolates each run in its own subprocess so one bad combination logs a failure instead of crashing the matrix.
Foundation Models & Reasoning Research
JEPA Implementation for Mathematical Reasoning & One-Shot RLVR
- Improved exact-match accuracy on MATH-style problems by 6–8% over an SFT baseline by implementing a Joint Embedding Predictive Architecture (JEPA) pipeline for mathematical reasoning on Qwen2.5-Math.
- Increased chain-of-thought correctness on GSM8K by 10% and reduced hallucinated reasoning steps by adapting RL pipelines (VERL/rllm) to fine-tune LLM policies with one-shot feedback (RLVR).
NLP Research
Hybrid DistilBERT–GAT for Relation Extraction
- Improved macro F1 on SemEval-2010 Task 8 by 4–6 points over a DistilBERT-only baseline by designing a hybrid DistilBERT + Graph Attention Network (GAT) architecture.
- Boosted classification precision on structurally complex sentences by 8–10% by integrating spaCy dependency parsing with custom graph attention layers.
End-to-End NLP Platform
Keyword News AI
- Reduced manual data preparation effort by 70% by engineering an end-to-end AI news platform in Python, LangChain, and Hugging Face Transformers to ingest, clean, and normalize unstructured data.
- Deployed an NLP summarization workflow with spaCy and Docker that generates concise, entity-preserving summaries, served via FastAPI to a React frontend.
LLM-Powered Agent
Stock Sense
- Reduced manual research time from 15–20 minutes to under 1 minute by building a LangChain-based AI agent that orchestrates tools for real-time market data, feature computation, and stock recommendations.
- Engineered Python pipelines for market ingestion, feature engineering, and LLM-assisted decision support, combining technical indicators with fundamentals.