Hey, I'm Aman Kushwaha
Full Stack Developer specializing in MERN stack & Next.js. Building scalable, performant web applications with clean code and great UX. Currently pursuing B.Tech in Computer Science.
Terminal
AAIPL Tournament: Dual-Agent Fine-Tuning Solution
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.
Genome AI: Cattle Breed Classification from SNP Data
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.
Conveyor Belt Detection
Labeled custom conveyor belt data and trained a YOLOv8 model from scratch. Increased detection accuracy from 72% to 80% with model tuning and augmentation.
RubricAI – Smart Academic Evaluation
RubricAI is a powerful Next.js application designed for educators and students to evaluate assignments against custom rubrics using Genkit AI. It features batch processing, Cloudinary file storage, and academic integrity monitoring.
