# Amrit Mohan - Developer Portfolio

Plain-text snapshot of Amrit Mohan's portfolio.

## About

Amrit Mohan is a computer science engineering student at Dayananda Sagar College of Engineering, Bengaluru. He focuses on AI systems, data pipelines, automation, RAG applications, and full-stack development.

## Contact

- Email: amritmohan200@gmail.com
- Phone: +91-8949678639
- GitHub: https://github.com/amrit-max
- LinkedIn: https://linkedin.com/in/amrit-mohan01
- Resume: /resume.pdf

## Education

Dayananda Sagar College of Engineering, Bengaluru
B.Tech, Computer Science and Engineering
2024 - 2028
CGPA: 8.45

## Technical Skills

- Languages: Python, C++, SQL
- AI and data: LangChain, LangGraph, RAG, NLP, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, PyTorch
- Tools: Git, GitHub, Jupyter Notebook, Google Colab, Pinecone, Power BI, Kaggle
- Databases: MySQL

## Experience

### Larsen & Toubro (L&T)

Project Trainee, Oct 2025 - Dec 2025

- Developed automated Python-based data extraction pipelines for machine health reports and equipment telemetry.
- Reduced manual reporting effort by 75% across 50,000+ equipment records.
- Built preprocessing and cleaning workflows that reduced analysis turnaround time by 60%.
- Designed Power BI dashboards for utilization and operational KPIs, cutting weekly reporting cycles from 6 hours to under 1 hour.

## Projects

### TriAge - Autonomous Quality Engineering Platform

Built a Healer Agent using LangGraph for automated RCA on test failures, commit correlation, and targeted fix patch generation through GitHub MCP PR workflows.

### WebRTC Video Conferencing Platform

Built a real-time peer-to-peer video conferencing app using WebRTC, JavaScript, WebSocket signaling, STUN/TURN traversal, and adaptive bitrate controls.

### Chat with Codebase - RAG-based Developer Assistant

Implemented a RAG pipeline with LangChain to clone repositories, parse source code, generate semantic embeddings, and support natural language codebase queries.

### Talk2Doc - AI Document Question Answering System

Built a RAG-powered document assistant for large documents with chunking, embeddings, LangChain retrieval, and contextual LLM response generation.

## Achievements

- 2x Hackathon Winner at Dayananda Sagar College of Engineering.
- 2x Hackathon Finalist in inter-college hackathons.

## Portfolio Stack

- Next.js 16
- React 19
- TypeScript
- Tailwind CSS v4
- Framer Motion
- shadcn-style primitives
- GitHub GraphQL API routes