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sujata-gaihre/README.md

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πŸ‘‹ Hi there, I'm Sujata Gaihre

🧠 Full Stack Developer | AI Researcher | Lifelong Learner from Nepal


πŸŽ“ Academic Journey

  • Master of Engineering in Computer Engineering – Pokhara University
    β†’ Graduated with Distinction (CGPA: 3.75/4.0)
    β†’ Thesis on Preterm Birth Risk Prediction using Hybrid ML Approach received Grade 'A'
    β†’ Awarded Full Scholarship for academic excellence

  • Bachelor of Engineering in Computer Engineering – Pokhara University
    β†’ Secured Full Merit Scholarship
    β†’ Graduated among top 5% of the cohort

My academic journey has been centered around developing robust technical foundations in computer science, data analytics, and machine learning. I’ve always been inclined toward building solutions that have practical impactβ€”be it in healthcare, education, or e-commerce.


πŸ’Ό Professional Experience

πŸš€ Software Engineer – Fusemachines (Aug 2022 – Present)

At Fusemachines, I work on cutting-edge AI products, full-stack web applications, and internal tools. I have contributed across several domains, especially on LLM-powered tools, secure backend APIs, and frontend dashboards.

Key Contributions:

  • πŸ” Developed AI-powered research assistant integrating Gemini and OpenAI APIs
  • 🌐 Designed and implemented GraphQL/REST APIs with authentication (AWS Cognito)
  • πŸ“ˆ Built reusable components and dashboards using React, Tailwind, and Storybook
  • πŸ€– Worked on AI-driven web crawler to extract, chunk, and vectorize content
  • πŸ“Š Created Price Simulation Platform with real-time forecasting and analytics

πŸ§ͺ QA Engineer – Outlines Research & Development (Feb–Jul 2022)

  • Designed and executed regression, API, and UI testing (Cypress, Selenium)
  • Wrote detailed bug reports and QA documentation

πŸ§ͺ QA Intern – Gamenic Nalamiz (Jun–Aug 2021)

  • Conducted manual testing for mobile and web-based games
  • Created structured test cases and collaborated in Agile environment

πŸ”¬ Research & Open Source Projects

🧠 ImageCLEFmed-MEDVQA-GI (CLEF 2025)

  • Developed a Visual Question Answering (VQA) system using Florence model
  • Co-authored accepted paper at CLEF 2025
  • πŸ“– arXiv Link

πŸ‘Ά Preterm Birth Risk Prediction (ME Thesis)

  • Applied hybrid clustering + ensemble learning (GMM + RF/GBM)
  • Metrics used: ROC AUC, PR AUC, Macro F1
  • πŸ“– ResearchGate Link

πŸ“˜ RAG-based Educational Assistant

  • Created a Retrieval-Augmented Generation chatbot
  • Used OpenAI + Pinecone for semantic document retrieval

πŸ§‘β€πŸ« Shikshyalay – Virtual Classroom

  • Built with Django, WebSockets (Channels)
  • Features: Real-time chat, file-sharing, Q&A, notification system
  • πŸ“– ResearchGate Link

🧰 Tech Stack

// Languages
Python | JavaScript | TypeScript

// Frontend
React | Next.js | Tailwind CSS | ShadCN | Bootstrap | HTML | CSS

// Backend
Node.js | Express | NestJS | REST | GraphQL | Swagger

// AI/ML
LLMs | Clustering | Transformers | OpenAI APIs | Gemini APIs | Scikit-learn

// Databases
PostgreSQL | MongoDB | SQL | Contentful

// Tools
Docker | Git | Postman | AWS Cognito | Storybook

// Testing
Cypress | Selenium | Unit Testing | Regression Testing

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