As a Full Stack Developer for an Italian publishing company, I contribute to a robust publishing platform that serves enterprises in producing and distributing digital books. My role encompasses diverse responsibilities to ensure smooth application operation and client satisfaction.Key Responsibilities:Application Maintenance: Ensure smooth running and regular updates of a TypeScript-based React application.Feature Development: Implement new features for backend (NestJS) and frontend (React.ts).Testing: Conduct unit testing with Jest and integration testing with Cypress.System Stability: Ensure changes do not break the application or Docker containers.Websocket Integration: Create websocket features for live notifications (e.g., order updates).State Management: Utilize Redux and Redux Toolkit for efficient state management.API Integration: Use RxJS and redux-observables for API calls and state updates.Dependency Management: Update the application, fixing breaking changes (Node.js, Yarn, TypeScript).Monorepo Setup: Implement Yarn workspaces for a monorepo, resolving sub-dependency issues.Bug Fixes: Identify and fix bugs and errors reported by clients.Technologies and Tools:Frontend: React.js, TypeScriptBackend: Node.js, NestJSState Management: Redux, Redux ToolkitTesting: Jest, CypressPackage Management: Yarn, Yarn workspacesReal-time Communication: Websockets, RxJS, redux-observablesContainerization: DockerVersion Control: GitThrough my work, I ensure high-quality code and regular updates, enhancing platform functionality and user satisfaction.

As a Machine Learning Engineer at Empirisch Tech, I was instrumental in developing and implementing advanced deep learning models. My work focused on ensuring the efficiency and effectiveness of our machine learning solutions, contributing to cutting-edge research and practical applications.Key Responsibilities:Model Development: Developed innovative deep learning models using PyTorch Lightning, with a focus on Neural Radiance Fields (NeRF).Model Deployment: Ensured smooth operation of deep learning and machine learning models in production.Environment Management: Managed WSL (Windows Subsystem for Linux) environments with Anaconda for model development and deployment.Computer Vision: Led Computer Vision projects for Object Identification, improving detection accuracy.Video Identification Model: Developed a model for identifying objects in live and pre-recorded videos.GitHub Integration: Utilized and forked relevant GitHub repositories to support project needs.Research and Documentation: Conducted research on new fields in Deep Learning, staying updated with the latest advancements.Technologies and Tools:Deep Learning Frameworks: PyTorch, PyTorch LightningEnvironment Management: Anaconda, WSLComputer Vision: OpenCV, custom modelsVersion Control: Git, GitHubResearch: Implemented knowledge from the latest research papers and documentationThrough my role at Empirisch Tech, I gained valuable experience in both practical application and research within Machine Learning and Deep Learning, contributing to innovative solutions.

I am currently working as a Teacher's Assistant for the course titled Operations Research in my current semester.

I worked as a testing agent for a new AI technology that Afiniti had built for its callers and workers.