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agarwalsoham993/README.md

Hi there, I'm Soham Agarwal 👋

🎯 About Me

I'm a full-stack developer and AI/ML enthusiast passionate about building production-ready systems that solve real problems. I specialize in:

  • Machine Learning & AI: practical models, embeddings, and RAG pipelines
  • Backend Systems: scalable APIs, microservices, and deployment infrastructure
  • Quantum Computing: quantum algorithms, optimization research, and prototypes
  • Computer Vision & Game AI: visual systems and intelligent agents

I focus on reproducible demos, clean APIs, and deployable prototypes at the intersection of research and product.

🛠️ Tech Stack

Python Go JavaScript TypeScript FastAPI Docker PyTorch TensorFlow AWS

🤝 Connect With Me

GitHub LinkedIn Medium YouTube Website


Continuously building and learning | Profile Views

 Soham Agarwal Profile

Soham Agarwal

🚀 Full-stack developer • AI/ML enthusiast

🎓 IIT Kharagpur

📊 GitHub Stats



🎯 Highlighted Projects

1. Code-Execution-Engine — Secure, Scalable Code Runner

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2. OpenBALC — Open source courses management and AI learning platform.

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3. CalendarSYNC —

  • Repo: https://github.com/Threnlabs/CalendarSYNC
  • Tech: Python, FastAPI, LLMs
  • Description: Intelligent Scheduling - Automatically find the best times for classes and meetings, ensuring a conflict-free schedule.
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4. GNN-QC — Graph Neural Networks × Quantitative Finance

  • Repo: https://github.com/agarwalsoham993/GNN-QC
  • Tech: PyTorch, Quantum Computing
  • Description: Exploratory research notebooks combining graph neural networks with small quantum circuits for hybrid quantum-classical prototyping.
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5. WhatsApp-RAG-Example — RAG Chatbot on WhatsApp

🚀 Key Focus Areas

Embeddings & Retrieval Systems

  • Open-source and cloud-hosted embedding models
  • Vector store integration (FAISS, Milvus, Pinecone)
  • Production-ready RAG pipelines for LLM applications

Quantum Algorithms & Optimization

  • Quantum circuit design and simulation
  • Hybrid quantum-classical algorithms
  • Optimization research with quantum-inspired methods

Scalable Backend Systems

  • Microservices architecture with FastAPI
  • Container orchestration and deployment
  • High-performance inference servers

MLOps & AI Orchestration

  • Agentic workflows and LLM orchestration (LangChain, AutoGen)
  • End-to-end model lifecycle management (MLflow, W&B)
  • Data pipeline automation and model deployment

📚 Current Work

I'm actively working on:

  • Advanced RAG systems and LLM tooling for production environments
  • Quantum algorithms for combinatorial optimization
  • Scalable backend infrastructure and distributed systems
  • Research prototypes that bridge theory and practical application

🤝 Connect With Me

GitHub LinkedIn Medium YouTube ![website](https://globe.img

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  1. Code-Execution-engine Code-Execution-engine Public

    A scalable, self-contained Code Execution Engine written in Go. Its core function is to execute user-submitted code in secure, isolated Docker containers and return the results via a simple REST API.

    Go 2

  2. Neural-Networks Neural-Networks Public

    Implementation and building of Neural Network from scratch in C++, with both forward and Backward Propagation.

    C++

  3. RAG RAG Public

    Retrieval Augmented Generation

    Python

  4. Docker Docker Public

    Python

  5. Market-basket-Analysis Market-basket-Analysis Public

    Implementing NLP and Machine Learning for real life problem faced in Shelf products placement in supermarket and purchase prediction.

  6. Unbeatable-tictactoe Unbeatable-tictactoe Public

    unbeatable tic tac toe game , using C++

    C++