Chenna
Kesava Reddy

→

I build intelligent systems — from training deep learning models to deploying production APIs and orchestrating cloud infrastructure. Currently pursuing B.Tech CSE, shipping real products along the way.

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0% Model Accuracy
0+ Users Served
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Chenna Kesava Reddy
96.82% CNN Accuracy
Containerized
CI/CD Ready
01 — About

Engineer by
discipline, builder
by nature.

I'm Chenna Kesava Reddy, an AI & Full Stack Developer based in Kadapa, Andhra Pradesh, India. I specialize in building end-to-end intelligent systems — from designing ML pipelines and training deep learning models to deploying them in production with containerized, cloud-native infrastructure.

Currently pursuing my B.Tech in Computer Science Engineering at RGMCET, Nandyal, while actively shipping projects that solve real problems. My work spans medical AI, security analysis, conversational AI, and educational tools.

Kadapa, AP, India B.Tech CSE (2026) Open to opportunities

AI & Machine Learning

Deep learning, CNNs, LLM integration, Hugging Face deployments, and explainable AI systems.

Full Stack Engineering

FastAPI & React.js applications with real-time features, REST APIs, and scalable database design.

DevOps & Cloud

Docker, Kubernetes, CI/CD pipelines, AWS/Azure deployments, and Linux server administration.

Security & Analysis

ML-based vulnerability detection, network scanning, and multi-threaded security analysis tools.

02 — Skills

Tech Stack

Tools and technologies I use to build production systems.

Programming

Python Java JavaScript SQL

Frontend

React.js HTML5 CSS3 Bootstrap

Backend

FastAPI Node.js Express.js REST APIs

Databases

PostgreSQL MySQL SQLite Supabase

AI / Machine Learning

PyTorch TensorFlow OpenCV Scikit-Learn Hugging Face LLM Integration Deep Learning CNNs

DevOps & Cloud

Docker Kubernetes Jenkins GitHub Actions Linux AWS Azure Nginx CI/CD

Tools

Git GitHub Postman VS Code
03 — Experience

What I've Built

Key milestones from my technical journey.

2025 — Present AI Engineering

AI Systems Developer

Independent / Open Source

  • Built and deployed a lung cancer detection CNN with 96.82% validation accuracy on Hugging Face Spaces with sub-3s inference.
  • Developed a full-stack ML security vulnerability analyzer using ensemble methods (XGBoost + Transformers) covering 12+ CVE categories.
  • Integrated multi-model AI chatbot (Cohere + LLaMA) with Supabase-backed chat history and 500+ users across deployments.
PyTorch Hugging Face FastAPI React.js
2024 Full Stack

Full Stack Developer

RGMCET College Project Lead

  • Led development of Faculty Selection System, deployed in real-time to serve 500+ students in under 3 minutes with live tracking logic.
  • Simultaneously shipped companion Android app in Java/XML via Android Studio for mobile-first access.
  • Coordinated a 53-contributor repository — the largest open-source collaboration in the college's history at the time.
React Java Android Studio SQL
2023 — 2024 Cloud & Certifications

Cloud & AI Foundations

Microsoft Azure · edX

  • Earned Microsoft Azure AI Fundamentals (AI-900) certification — validated understanding of ML concepts, Azure AI services, and responsible AI.
  • Completed HTML5/CSS and Raspberry Pi IoT platform courses from edX, building hardware-software bridge skills.
Azure AI-900 IoT
04 — Projects

Featured Projects

Production-deployed systems with real users and measurable results.

AI / Document Intelligence Multi-provider AI

DDR-AI Report Generator

AI-powered document intelligence platform that transforms engineering inspection PDFs into structured Detailed Defect Reports by extracting text, analyzing thermal images, detecting defects, assessing risks, and generating professional downloadable reports within seconds.

  • Multi-provider AI pipeline using Gemini, Claude & OpenAI for intelligent defect detection and risk assessment
  • Advanced PDF extraction with PyMuPDF, pdfplumber & OCR supporting text, tables, and thermal images
  • FastAPI backend with automated ReportLab PDF generation deployed on AWS Amplify & AWS EC2
FastAPI AWS Amplify AWS EC2 Gemini AI Claude AI OpenAI PyMuPDF OCR ReportLab
Live Demo
AI / Medical 96.82% accuracy

Lung Cancer Detection System

Deep learning pipeline that analyzes CT scans to detect and classify lung cancer nodules with medical-grade reliability. Deploys in under 3 seconds on Hugging Face.

  • Custom CNN + ResNet50 pipeline achieving 96.82% validation accuracy
  • Integrated segmentation & Grad-CAM heatmap for nodule localization
  • Gradio UI deployed on Hugging Face Spaces, accessible globally
PyTorch OpenCV Gradio Hugging Face CNN
Live Demo
AI / Chatbot Multi-model

Multi-Model AI Chatbot

Intelligent chatbot integrating Cohere and LLaMA for context-aware responses, with secure Supabase-backed chat history and a responsive React UI.

  • Dual-model routing — Cohere for fast responses, LLaMA for deep reasoning
  • Supabase Realtime for persistent, secure conversation history
  • Responsive React UI with streaming response support
React Cohere API LLaMA Supabase JavaScript
View Demo
Security / ML 12+ CVE types

Security AI Vulnerability Analyzer

Full-stack ML security platform that analyzes code and network targets for vulnerabilities using ensemble ML with human-readable AI explanations.

  • Ensemble XGBoost + Transformer pipeline covering 12+ vulnerability classes
  • Multi-threaded network scanning with BeautifulSoup web content analysis
  • Explainable AI engine surfaces actionable remediation suggestions
Python XGBoost Transformers Gradio BeautifulSoup
Live Demo
Full Stack 500+ students

College Management System

Real-time faculty selection platform serving 500+ students simultaneously, with live tracking logic, fairness constraints, and a companion Android app.

  • Handles 500+ concurrent students with sub-3-minute faculty assignment cycles
  • Live tracking with UI-driven fairness constraints baked into selection logic
  • Android companion app in Java/XML deployed alongside the web version
React Java Android Studio SQLite
Live Site
AI / Education 500+ users
In Progress

AI Tutor Platform

Adaptive learning platform powered by LLMs that generates personalized quizzes, explanations, and learning paths based on a student's performance history.

  • LLM-backed adaptive curriculum with real-time difficulty adjustment
  • FastAPI backend with React frontend, PostgreSQL for user state
  • Tracks learning velocity and surfaces knowledge gaps automatically
FastAPI React LLM PostgreSQL Hugging Face
Coming Soon
05 — DevOps

Infrastructure Mindset

From local Docker containers to Kubernetes clusters — I build with deployment in mind.

CI/CD Pipeline

GitHub Actions
git push
Tests
Docker Build
Registry Push
Deploy

Docker Deployment

FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 8000
CMD ["uvicorn", "main:app"]

Kubernetes Architecture

Ingress Controller
Service
Service
Pod ×3
Pod ×2
Persistent Volume

AWS Deployment Architecture

Production-ready
Users
↓
CloudFront CDN
↓
Application Load Balancer
↓
EC2
EC2
EC2
RDS PostgreSQL
S3 Storage
Git Flow

Git Workflow

Interactive visualization of Git data flow — from working directory to remote repository.

Git Workflow

Visualizing Git Data Flow
10 — Pipeline

From idea to
production, traced.

Every project I ship moves through the same disciplined pipeline — ten stages, one continuous loop back to improvement.

01
Shipped

Idea

Spot a real problem worth solving — the spark behind every build.

Problem framing Feasibility
02
Shipped

Research

Study prior art, constraints, and users before committing to a direction.

Requirements Tech scouting
03
Shipped

UI/UX Design

Wireframe the flow, then design and prototype the real interface.

Wireframes Prototyping
04
Shipped

Architecture

Design the system shape — services, data flow, and failure modes — before writing code.

System design Data modeling
05
In progress

Development

Build the frontend, backend, and AI pipeline in tight, testable increments.

React FastAPI LLM pipelines
06
In progress

Testing

Debug edge cases, verify responsiveness, and profile performance under load.

Debugging Responsive QA
07
Queued

Deployment

Ship through CI/CD — containerized builds pushed straight to production.

GitHub Actions Docker
08
Queued

AWS + Cloudflare

Cloud infrastructure and edge delivery — compute, storage, DNS, and CDN.

EC2 / Amplify Cloudflare
09
Planned

Monitoring

Watch the system in production — uptime, errors, latency, and real usage.

Logging Analytics
10
Planned

Continuous Improvement

Feed monitoring data back into research — the loop that never really ends.

Feedback loops Iteration
06 — Certifications

Credentials & Certifications

Microsoft

Azure AI Fundamentals

AI-900 2024
View
edX
edX

HTML5 & CSS Fundamentals

Web Development 2023
View
edX

Raspberry Pi Platform

IoT / Embedded 2023
View
07 — GitHub

GitHub Activity

GitHub Stats for Chenna Kesava Reddy Top Languages for Chenna Kesava Reddy
GitHub Contribution Graph
08 — Education

Academic Background

2023 — 2026

B.Tech — Computer Science Engineering

Rajeev Gandhi Memorial College of Engineering & Technology (RGMCET), Nandyal

7.0 CGPA AI/ML · Web Dev · Systems
2021 — 2023

Diploma — Computer Science Engineering

Government Polytechnic College, Proddatur

69.9%
2019 — 2020

SSC — Secondary School Certificate

Pavan Concept School, Kadapa

10.0 CGPA Perfect Score
09 — Contact

Let's build
something great.

Open to full-time roles, freelance projects, and research collaborations. I respond within 24 hours.

Email chenna.dev@chennareddy.in
Phone +91 77028 50533
Location Kadapa, Andhra Pradesh, India
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