About
Work
PharmEasy
|Software Development Engineer Intern
Summary
Contributed to Genie Bot, an automation system that extracts and processes purchase orders from email attachments, reducing manual effort by 80% and processing 500+ orders daily with 95% accuracy. Collaborated on Genparser, a scalable document parser leveraging Google Vertex AI to extract structured data from unstructured documents like invoices and lab reports. Developed prompt-based parsing workflows and supported asynchronous task execution using Celery and Redis, with file storage managed via Google Cloud Storage.
Education
National Institute of Technology Raipur
Master
Computer Applications
Grade: 8.26
University Institute of Technology, Kanpur
Bachelors
Computer Applications
Grade: 7.5
Awards
Knight Rating 1824 badge
Awarded By
Leetcode
Achieved Knight Rating 1824 badge on Leetcode and Specialist Rating 1407 on Codeforces
Finalist at Vigyaan
Awarded By
NIT Raipur for Machine Learning Project
Finalist at Vigyaan an inter college Hackathon organized by NIT Raipur for Machine Learning Project.
Skills
Languages
Java, Python, Javascript, C++.
Technologies
Flask, React.js, Express.js, TensorFlow, Node.js, Spring, Spring Boot, Maven.
Subjects
Operating System, OOPS, DBMS, Networking, Data Structure and Algorithms.
Dev Tools
GitHub, VS Code, Kuberntetes, Jenkins, Jupyter, Docker, Rabbitmq.
Databases
MySQL, MongoDB, Postgres.
Projects
Sprinter Performance Analysis
Summary
Developed a real-time performance analysis application for sprinters using the CNN Movenet lightning Model for precise pose estimation. Conducted training on a multivariate regression model using data from 30 Olympians (sprinters) to predict optimal values for critical parameters such as stride length, arm angle, hip-knee angle, etc. Implemented a comprehensive feedback system by comparing actual parameter values to predicted ones, offering valuable insights for performance improvement. Leveraged Streamlit to create an intuitive and interactive application, enhancing accessibility and usability for coaches and athletes.
Workify
Summary
Developed Workify, a scalable job management service using a microservices architecture to enhance flexibility and scalability. Enabled interaction with job listings, company details, and user reviews through REST APIs, allowing for efficient data access and manipulation. Employed Docker for containerization to maintain consistent deployment environments across various stages of development. Utilized PostgreSQL for robust data storage and RabbitMQ for asynchronous communication between services, improving system performance and reliability.