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ChaitanyaSaik/README.md

Typing SVG


LinkedIn GitHub Email

🧠 About Me

class ChaitanyaSaiKurapati:
    def __init__(self):
        self.role         = "AI/ML Engineer | Full-Stack Developer"
        self.education    = "B.Tech CSE @ Amrita Vishwa Vidyapeetham (2022–2026)"
        self.cgpa         = 8.47
        self.focus        = ["LLMs", "RAG Architectures", "Distributed Systems", "Production ML"]
        self.publications = ["ICCATEET 2026", "IEEE INDISCON 2025"]
        self.leetcode     = "250+ problems solved | Top 15%"
        self.motto        = "Ship to production, not just notebooks."

    def current_work(self):
        return "AI-powered Resume Intelligence @ Alpxin Technologies"

    def ask_me_about(self):
        return ["LangChain", "FAISS", "FastAPI", "PyTorch", "Apache Spark"]

🛠️ Tech Stack

🐍 Languages

Python Java SQL

🤖 AI / ML / LLM

PyTorch Scikit-Learn HuggingFace LangChain OpenAI XGBoost

⚙️ Backend & APIs

FastAPI Flask Streamlit

🗄️ Databases

MySQL PostgreSQL

☁️ Cloud & Big Data

AWS Apache Spark

📚 Publications

📄 Multi-Label Chest X-Ray Diagnosis

ICCATEET 2026

Proposed a hybrid Vision Transformer + DenseNet architecture for multi-label disease classification on chest X-rays. Achieved 94.2% accuracy and 0.96 AUC across 14 pathological categories.

📡 TCP vs UDP in Multi-Robot Systems

IEEE INDISCON 2025

Comparative analysis of TCP and UDP communication protocols in multi-robot coordination environments, with latency benchmarking and reliability tradeoff analysis under real-world noise conditions.

🏆 Achievements

🥇  Hackathon Finalist — Top 8 out of 120 teams  |  💻  250+ LeetCode problems — Top 15% globally

👨‍🏫  Mentored 15+ students in Data Structures & Algorithms  |  ✍️  Published technical articles on AI & ML

📖  2× Peer-Reviewed Publications (IEEE + ICCATEET)  |  ⚡  AI/ML Intern @ Alpxin Technologies

💼 Experience

🏢 AI/ML Intern — Alpxin Technologies (Apr 2025 – Jul 2025)

  • 🎯 Built an AI-powered Resume Intelligence System achieving 80% accuracy in job-to-resume matching
  • 🔍 Improved resume parsing and semantic similarity using Sentence Transformers + FAISS
  • 🧩 Designed a skill-gap detection pipeline leveraging LLMs for targeted candidate feedback
  • 🚀 Deployed end-to-end scalable system using FastAPI + Streamlit with production-ready architecture

🎯 Currently Focused On

┌──────────────────────────────────────────────────────────┐
│  🔭 Scalable ML systems for production workloads         │
│  🧪 Advanced LLM + RAG architectures                     │
│  ☁️  Cloud-native AI deployment (AWS + Docker)           │
│  📊 Distributed data engineering with Apache Spark       │
│  🎓 Graduating May 2026 — Open to MLE / SDE Roles        │
└──────────────────────────────────────────────────────────┘

🤝 Let's Connect

I'm always open to collaborating on AI/ML projects, discussing research ideas, or exploring full-time opportunities.

LinkedIn Email GitHub

"The best model is the one that's running in production."

⭐ If you find my work valuable, consider starring a repo — it means a lot!

Pinned Loading

  1. Evaluating-TCP-vs.-UDP-in-Centralized-Multi-Robot-Communication-using-Star-Topology Evaluating-TCP-vs.-UDP-in-Centralized-Multi-Robot-Communication-using-Star-Topology Public

    This project presents a MATLAB-based simulation framework that evaluates the performance of TCP (Transmission Control Protocol) and UDP (User Datagram Protocol) in a centralized multi-robot communi…

    MATLAB 1

  2. SIPA-Real-Time-AI-Interview-Preparation-Assistant SIPA-Real-Time-AI-Interview-Preparation-Assistant Public

    A comprehensive AI-powered platform designed to help job seekers excel in technical interviews through intelligent resume analysis, mock interview simulations, and personalized learning paths.

    Python 1

  3. Distributed-Data-Processing-using-PySpark Distributed-Data-Processing-using-PySpark Public

    This project demonstrates a scalable data processing pipeline using Apache Spark (PySpark) to handle large datasets efficiently. The focus is on comparing distributed computing with traditional seq…

    Jupyter Notebook

  4. Intelligent-AutoML-Engine-for-End-to-End-Data-Analysis-Predictive-Modeling Intelligent-AutoML-Engine-for-End-to-End-Data-Analysis-Predictive-Modeling Public

    An end-to-end ML & DL workflow automation platform built with Streamlit that empowers users to train, evaluate, visualize, and deploy machine learning models seamlessly — without writing code. It s…

    Python

  5. Multi-Label-Chest-X-Ray-Diagnosis-using-Vision-Transformers-and-CNNs Multi-Label-Chest-X-Ray-Diagnosis-using-Vision-Transformers-and-CNNs Public

    A deep learning research project comparing Vision Transformers (ViT) and DenseNet121 CNN for multi-label chest disease classification using the NIH ChestX-ray14 dataset.

    Jupyter Notebook