ANUPAM MALVIYA

Kanpur, IN.

Work

PharmEasy

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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

Leetcode

Achieved Knight Rating 1824 badge on Leetcode and Specialist Rating 1407 on Codeforces

Finalist at Vigyaan

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

Meetcode

Summary

Developed a platform enabling users to solve a wide range of coding problems and submit their solutions for immediate evaluation. Implemented features allowing users to create and share their own coding problems, promoting a collaborative and interactive environment.

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.