Raj Kumar Satya Rapeti

Analytically driven Computer Science student with hands-on experience in building dynamic, data-driven applications and implementing cloud-based solutions to solve complex problems. Skilled in leveraging technology and analytics to drive insights and efficiencies in real-world projects, making a meaningful impact.

Other Projects

1. Data-Driven Portfolio Tracker

• Description: Build a web app that helps users track and analyze their investment portfolios. It retrieves real-time financial data, offers insights on asset performance, and calculates metrics like ROI and volatility.
• Technologies:
• Frontend: React (part of the MERN stack) for an interactive user interface.
• Backend: Node.js and Express to create a REST API that retrieves and serves financial data.
• Database: MongoDB to store user portfolios and historical transaction data.
• Data Processing: Python to process and analyze financial metrics, such as calculating portfolio diversification and growth trends.
• APIs: Integrate with financial data APIs (e.g., Alpha Vantage or Yahoo Finance).
• Features:
• Allow users to add, edit, and remove assets from their portfolio.
• Visualize portfolio performance over time with charts.
• Provide personalized recommendations based on asset performance and trends.

2. Personalized News Aggregator with Topic-Based Filtering

• Description: Build a web application that aggregates news articles based on user-selected topics, delivering tailored content with filters for real-time and historical data analysis.
• Technologies:
• Frontend: React for a clean and customizable news dashboard.
• Backend: Node.js and Express to fetch news articles from APIs like NewsAPI or Bing News.
• Database: MongoDB to store user preferences and cached articles.
• Data Analysis: Python to process and filter news content based on sentiment and relevance.
• Features:
• Allow users to set topics of interest and personalize news feeds.
• Include sentiment analysis on articles to highlight positive, neutral, or negative news.
• Offer charts showing news trends (e.g., frequency of articles on a topic over time).

3. Task Management App with Productivity Analytics

• Description: Develop a task management tool that allows users to track their to-do list while analyzing productivity and time spent on various tasks.
• Technologies:
• Frontend: React to create an interactive, drag-and-drop task board.
• Backend: Node.js and Express to handle task creation, updates, and deletions.
• Database: MongoDB to store user data and task history.
• Data Analytics: Python to analyze task completion rates and productivity trends.
• Features:
• Track tasks with categories, priorities, and deadlines.
• Provide productivity reports based on task completion and time spent on different task types.
• Include visualizations (e.g., time allocation per category, weekly productivity).

4. Real-Time Collaboration Tool with Document Sharing

• Description: Build a web-based collaboration tool for teams to share and edit documents in real-time, with live updates and a user activity feed.
• Technologies:
• Frontend: React for a dynamic, real-time interface with live document editing.
• Backend: Node.js and Express for handling document data and user sessions.
• Database: MongoDB to store document versions and user activity.
• Real-Time Communication: WebSocket or Socket.io for live updates.
• Features:
• Allow multiple users to edit the same document, with changes reflected in real-time.
• Include an activity feed to track document changes and user actions.
• Add document versioning so users can revert to previous versions if needed.

5. Customizable Survey Builder and Analysis Tool

• Description: Create a survey platform that lets users build custom surveys, collect responses, and analyze results, ideal for businesses looking to gather feedback.
• Technologies:
• Frontend: React for creating a drag-and-drop survey builder and response dashboard.
• Backend: Node.js and Express to manage survey data and responses.
• Database: MongoDB to store survey configurations and response data.
• Data Analysis: Python to analyze response data, providing insights and visualizations.
• Features:
• Users can build surveys, send them to respondents, and view responses in real-time.
• Provide analytics, like sentiment analysis for text responses and charts for multiple-choice answers.
• Include response summaries and downloadable reports.

6. Inventory Management System

Description: Create an inventory management application with a Java backend to handle inventory data and a MERN stack frontend for managing stock.

• Technologies:
• Backend: Java (Spring Boot) for inventory operations.
• Frontend: MERN Stack (MongoDB, Express, React, Node.js) for the dashboard.
• Database: MongoDB for storing inventory details.
• Features:
• Add, update, and delete inventory items.
• Track stock levels and set alerts for low stock.
• Provide visual analytics on inventory levels, turnover, and trends.