SANTHOSHI KONDAPARTHY

Computer Science graduate possessing robust expertise in data structures and algorithms, coupled with practical experience in backend application development and RESTful API creation using Python (Flask). Skilled in crafting secure authentication processes, modular codebases, and database-centric systems. Exhibits exceptional problem-solving and analytical capabilities, adept at translating core CS principles into practical software solutions. Effective team collaborator with experience contributing to end-to-end project development

1.Automated Email Categorization System

Tech Stack: Python, Flask, MongoDB, Gmail API, OAuth 2.0

• Designed an intelligent email filter utilizing Natural Language Processing (NLP) libraries to classify text into priority buckets based on keyword frequency and semantic analysis.
• Architected a secure authentication flow using OAuth 2.0 to interface with the Gmail API, ensuring scoped access control and protecting user credentials.
• Developed a RESTful backend in Flask to handle tokenization and text preprocessing, structuring the application for future scalability and model retraining.
• Implemented a modular data pipeline capable of parsing complex JSON payloads from the Gmail API and storing structured metadata in MongoDB.

2.Algorithmic Task Scheduling Engine

Tech Stack: Python, Flask, MongoDB Greedy Algorithms

• Engineered a task optimization system implementing the Earliest Deadline First (EDF) Greedy algorithm to logically minimize task overlap and maximize daily throughput.
• Built a conflict-detection mechanism using interval scheduling logic, ensuring data integrity when users attempt to book overlapping time slots.
• Designed the backend architecture with Python and Flask to support dynamic CRUD operations, allowing real-time schedule adjustments without system downtime.

3.Roadside Assistance Platform

Tech Stack: Python, Flask, MongoDB, REST APIs

• Architected a location-based discovery engine that acts as a transparent middleware, matching user distress location with the nearest registered service providers in real-time.
• Implemented a geospatial retrieval system where users enter their location to instantly view relevant service providers. Enhanced the data model to return embedded Google Maps links, enabling users to view precise provider locations on the map."
• Designed a dual-schema database architecture: one collection to securely ingest dynamic user requests (vehicle type, location, issue urgency) and another to store static provider metadata for read-heavy retrieval.
• Built a fault-tolerant REST API to ensure 24/7 service availability, exposing direct contact details of providers to reduce friction during emergency roadside scenarios.