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Selected work

Things I've built.

Products, tools and experiments — mostly full-stack web work, increasingly with a machine learning component. Each entry links to a write-up where there is one.

VoxRAG website
completed

VoxRAG

featured

VoxRAG is a voice- and text-enabled Retrieval-Augmented Generation system built on MSMARCO-XI. Speak or type in English, हिन्दी, मराठी, বাংলা, മലയാളം, ગુજરાતી, অসমীয়া — the pipeline transcribes, retrieves grounded passages from ~3.2M (32 lakh) embedded records, and streams a cited answer back, targeting <200 ms retrieval / time-to-first-token.

  • Python
  • Streamlit
  • SarvamAI
  • Groq
IITD_Feb26_AAIPL
completed

Won the AAIPL Hackathon (1st place out of 120 teams) by building a dual-agent LLM system using Qwen2.5-14B-Instruct. Developed end-to-end fine-tuning pipelines with LoRA and 4-bit quantization to train a Question Agent for generating MCQs and an Answer Agent for solving them with structured reasoning. Implemented robust data cleaning, custom dataset formatting, and efficient training workflows for high performance under constrained compute.

  • Python
  • Jupyter Notebook
  • UnSloth
  • LoRa
The Diary Profile Page
development

The Diary is a minimal, distraction-free social platform built for busy professionals to stay connected with family and close friends through daily journal entries and quick personal notes—without the clutter of traditional social media.

  • Nextjs
  • Postgresql
  • Tailwind CSS
  • Prisma ORM
Main AkashSetu Web Page
completed

AkashSetu

featured

AI-enabled detection of exoplanets from noisy TESS light curves, using a Box-Least-Squares transit search feeding a calibrated XGBoost + Random-Forest ensemble, plus an LLM (via Groq) that explains and discusses each result with you.

  • Python
  • Jupyter Notebook
  • XGBoost
  • Groq
Genome AI: Cattle Breed Classification from SNP Data preview
completed

A reproducible machine learning pipeline for cattle breed classification from SNP genotype data, featuring CNN and Transformer baselines. Includes data validation, preprocessing, training, and benchmarking workflows to compare local vs long-range genomic pattern modeling.

  • Python
  • Jupyter Notebook
  • PLINK
  • NumPy
Conveyor Belt Detection preview
completed

Labeled custom conveyor belt data and trained a YOLOv8 model from scratch. Increased detection accuracy from 72% to 80% with model tuning and augmentation.

  • Python
  • OpenCV
  • Roboflow
  • YOLOv8 (Ultralytics)