Skip to content
View nagateja-naidu's full-sized avatar

Block or report nagateja-naidu

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
nagateja-naidu/README.md

Hi πŸ‘‹, I'm Boya Nagateja Naidu


πŸš€ About Me

I'm a Computer Science undergraduate specializing in Data Science and currently working as an AI Research Intern in an AI Engineer role.

My work focuses on developing research-grade AI systems using Machine Learning, Deep Learning, and Natural Language Processing. I'm currently involved in projects centered around Conditional Variational Autoencoders (CVAEs), synthetic data generation, and continuously expanding my expertise in Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs).

Alongside research, I actively strengthen my problem-solving skills through Data Structures & Algorithms (Java) while contributing to AI open-source projects, with the goal of building scalable, production-ready AI applications.

πŸ’‘ Focus Areas

  • πŸ€– Machine Learning & Deep Learning
  • 🧠 Natural Language Processing (NLP)
  • πŸ“š Retrieval-Augmented Generation (RAG)
  • πŸ”¬ Generative AI & Large Language Models
  • 🧬 Conditional Variational Autoencoders (CVAEs)
  • ⚑ Data Structures & Algorithms (Java)
  • 🌍 Open Source AI Development

Passionate about transforming AI research into practical, scalable solutions through engineering, experimentation, and continuous learning.


πŸ› οΈ Tech Stack

πŸ€– AI / Machine Learning

πŸ’» Programming Languages

🌐 Web Development

πŸ—„οΈ Databases & Cloud

βš™οΈ Developer Tools


🎯 Current Focus

  • πŸ”¬ Building research-grade AI systems using Conditional Variational Autoencoders (CVAEs)
  • πŸ€– Developing Retrieval-Augmented Generation (RAG) applications
  • 🧠 Exploring Large Language Models (LLMs) and Generative AI
  • βš™οΈ Designing scalable AI applications using Machine Learning, Deep Learning, and Natural Language Processing
  • 🌍 Contributing to AI Open Source projects
  • πŸ’» Strengthening Data Structures & Algorithms (Java) for software engineering

Luffy Smiling

πŸ“Š GitHub Statistics


πŸ”₯ GitHub Streak


πŸ“ˆ Contribution Graph


🌟 Highlights

  • πŸš€ AI Research Intern working in an AI Engineer role
  • 🀝 Active Open Source Contributor
  • 🧠 Developing research-grade AI systems
  • πŸ“š Exploring Retrieval-Augmented Generation (RAG) & Large Language Models
  • πŸ’» Building end-to-end AI applications using FastAPI and modern ML frameworks

🌍 Open Source

  • 🀝 Contributing to AI & Machine Learning open-source projects
  • πŸš€ First contribution submitted to the PyTorch-VAE repository
  • πŸ“ˆ Continuously expanding contributions to the AI open-source ecosystem

πŸ“« Connect With Me

Popular repositories Loading

  1. Taskflash-Frontend Taskflash-Frontend Public

    HTML

  2. TaskFlash TaskFlash Public

    HTML

  3. Snack-Alert Snack-Alert Public

  4. databricks-14-day-ai-challenge databricks-14-day-ai-challenge Public

    Jupyter Notebook

  5. End-to-end-Machine-Learning-Project-with-ML-flow End-to-end-Machine-Learning-Project-with-ML-flow Public

  6. Logistics-Route-Efficiency-Scoring Logistics-Route-Efficiency-Scoring Public

    Logistics companies need a scoring framework to compare delivery routes. ML can score route efficiency using synthetic distance, traffic, and time variables