Gabriel Arellano Email and Phone Number

• Added front-end error handling in ReactJS, providing notifications in both English and Spanish• Implemented Google Analytics, significantly enhancing website tracking accuracy across various environments.• Enhanced Java Spring Boot backend through various optimizations, feature additions, bug fixes, and improvements,leading to increased code readability and seamless frontend communication.• Adept in using Cypress for end-to-end and component testing of a web application.• Managed Azure App Config, leading to enhanced efficiency in configuration management.• Converted backend code to asynchronous processing, reducing response time across multiple microservices.• Proficient in Swagger, with experience migrating backend code and microservices from Swagger Springfox to Swagger Springdoc, adding new API information and implementing updated documentation for improved clarity.• Modified frontend code with Redux states to reflect real-time changes.• Utilized Azure Infrastructure as Code for deployment across multiple environments, actively monitoring and troubleshooting Azure CI/CD pipelines.

• Developed RESTful APIs for EV charging management solutions which enabled telematics functionality including the ability to retrieve data such as location and vehicle trip information.• Created algorithm to organize asynchronous JSON messages between microservices using message brokers in a queue to ensure proper storage in PostgreSQL database for an Open Charge Point Protocol implementation.• Automated properties file creation, eliminating manual additions, which improved system code readability and efficiency.• Added localization to Java Spring Boot project for multi-language support.• Wrote Spring Boot integration tests and validated endpoints with Postman to ensure correct API functionality.• Enabled energy load forecasting to reduce energy consumption and manage energy load in a power grid through the useof Protocol Buffers by parsing and serializing data to and from Azure Eventhub.• Built an event logging system within service and repository classes for efficient project monitoring.• Identified and resolved system vulnerabilities using MEND analysis tool.• Utilized Docker to launch project environments and customize environment settings for development and testingpurposes.• Created and kept up-to-date documentation for team reference on newly introduced features

Designed, tested, and implemented an image segmentation algorithm and convolutional neural network to classify worker bees and drones with Python, OpenCV, TensorFlow, and Keras.● Increased accuracy of existing bee recognition program by over 40 percent using background subtraction algorithm• Adapted an existing system to expedite creation of datasets for network training. • Used image segmentation to separate bees from video feed.• Installed operating systems on Raspberry Pi’s to carry out testing and application of an embedded system using various sensors.