Hari charan Reddy Yalla

Hari charan Reddy Yalla

Final-Year CSE Student | IEEE Computer Society | AI & Software Development Enthusiast

Hyderabad, Telangana, India

yallaharicharanreddy2005@gmail.com


About

I am a final-year B.Tech Computer Science and Engineering student at Anurag University, passionate about Artificial Intelligence, software development, and emerging technologies. Currently serving as the Chair of the IEEE Computer Society Student Branch Chapter at Anurag University, I actively contribute to technical initiatives, student engagement, and community building. I am also an IEEE Computer Society Richard E. Merwin Student Scholarship recipient (Spring 2026). My technical experience includes Python, Java, SQL, FastAPI, Flask, and AI API integrations. I have worked on projects involving AI-powered applications and automated workflows, gaining practical experience in software development and problem-solving. I enjoy collaborating with like-minded people, exploring new technologies, and building solutions that create meaningful impact. I am eager to learn, grow as a software professional, and contribute to innovative projects.

Skills
Python
Product Management
PostgreSQL
TensorFlow
Gemini
Firebase
Android
Java
Projects

Cosmic AI – AI-Powered Web Application

Cosmic AI is an interactive web application that integrates artificial intelligence capabilities into a unified user-friendly platform. Developed using Python and Flask, the application leverages the Google Gemini API for AI-powered conversational interactions and the Hugging Face API for AI-based functionality, including prompt-driven image generation. Google Translate integration enables multilingual translation, making the application more accessible to users from different linguistic backgrounds. The project combines AI API integration, backend development, and interactive web technologies to deliver multiple intelligent features through a single interface. It demonstrates how existing AI services can be integrated into practical applications without building machine learning models from scratch.

Python
Flask
Google Gemini API
Hugging Face API
Google Translate API
HTML
CSS
JavaScript

RefundOps – Automated Refund Management System

RefundOps is an automated refund management system developed to streamline refund processing and reduce repetitive manual operations. Built using Python and FastAPI, the application provides backend APIs for managing refund requests, validating information, and tracking refund statuses. Playwright is integrated to automate browser-based workflows, enabling interactions with web applications as part of the refund process. The system also incorporates the Google Gemini API to support AI-powered processing within the workflow. Its modular architecture helps maintain organized business logic and supports future enhancements. The project demonstrates the practical application of backend development, browser automation, API integration, and AI-assisted workflow automation.

Python
FastAPI
Playwright
Google Gemini API
REST APIs

CareerPilot AI – AI-Powered Career Preparation Platform

CareerPilot AI is an AI-powered career preparation platform designed to help students and job seekers improve their career readiness through personalized guidance and intelligent automation. The platform analyzes resumes, evaluates ATS compatibility, matches candidate profiles with job descriptions, and identifies skill gaps to help users understand areas for improvement. It also supports interview preparation through AI-generated interview questions, mock interview feedback, and personalized career recommendations. Additional features include cover letter generation, career progress tracking, and a centralized dashboard to monitor professional development. The platform aims to simplify the job preparation process by bringing essential career development tools into a single, intelligent application.

Python
FastAPI
React.js
PostgreSQL
Google Gemini API
REST APIs

Smart Community Health Monitoring and Early Warning System for Water-Borne Diseases

This project focuses on developing a machine learning-based early warning system to assess the risk of water-borne diseases in rural communities across Northeast India. The system analyzes environmental and water quality parameters, including pH, turbidity, dissolved oxygen, conductivity, rainfall, and temperature, to identify potentially unsafe water conditions and estimate associated health risks. An interactive dashboard presents water quality indicators, risk classifications, and visualized trends to help users understand changing environmental conditions. The system also provides preventive recommendations to promote awareness and support timely intervention. The project combines machine learning, environmental data analysis, and data visualization to explore how technology can contribute to public health monitoring and early risk detection.

Python
Machine Learning
Pandas
NumPy
Scikit-learn
Data Visualization
HTML
CSS
JavaScript
Education

Computer Science and Engineering

Anurag University · 8.67

Jul 2023 to May 2027