Krishna Siddhardh

Software Developer at BeeHyv Software Solutions (2022-11 – 2023-06)

Designed and implemented a dynamic web application using Python, Django, and React, enabling real-time data interaction and updates for agricultural task management across large, diverse land areas, exceeding client expectations by implementing real-time calculation features not initially required.
Built and deployed a full-stack web application using Django REST Framework for CRUD operations, React for front-end development, PostgreSQL for database management, and Docker for seamless deployment to in-house servers.
Optimized back-end performance by rewriting critical calculation functions in C, resulting in a 200% improvement in processing speed compared to original Python implementation.
Managed development of a Kotlin-based Android application using Jetpack Compose, reducing development time by 50% and introducing modern UI practices to the company.
Led a team of four developers, ensuring delivery of clean, maintainable, and bug-free code while maintaining regular client communication to align product development with their vision and requirements.
Contributed to a Spring-based application by developing APIs and functionalities and provided support for Android app development in a separate project.

Project Engineer at Wipro Limited (2021-07 – 2022-10)

Built a Python-based machine learning algorithm to detect and visualize defects in wooden electrical poles, replacing a square-based method with an innovative radial mathematics approach to actually see where the defects exactly are.
Achieved 95% accuracy in defect detection by implementing complex radial calculations and leveraging ultrasound data for enhanced defect visualization.
Optimized algorithm performance by 100% through data preprocessing techniques, enabling real-time processing on mobile platforms (Android/iOS) via cloud integration.
Contributed to Flutter app development, focusing on data collection and algorithm integration, and built Flask API endpoints to seamlessly deploy the ML model for web and mobile use.
Constructed a user-friendly React-based website to enhance project accessibility and usability.
Presented the project solo to the CTO during COVID, securing continued funding amid widespread project cuts.

Software Engineer Intern at Wheebox (2019-08 – 2019-12)

Designed and developed a web application to analyze exam data, including user responses, question performance, and topic-level insights, enabling creation of a dynamic difficulty system for exams.
Built the application using MySQL for database management, Java Spring Boot for API development, Hibernate for database connectivity, Tomcat for API deployment, and AngularJS for front-end interface.
Implemented APIs to provide metrics such as attempt rate, solution accuracy, and time taken for individual questions and users, enhancing data-driven decision-making.
Developed an AI algorithm to predict copying during exams using deep neural networks with 77% accuracy, laying the foundation for future improvements in cheating detection.

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