I have gained extensive experiences indeveloping full-stack web applications and working with various technologies. With a strong foundation in computer science and hands-on experience in developing full-stack applications, I am eager to apply my skills and knowledge to new and exciting projects in the field. I thrive in collaborative environments, and I am always enthusiastic about learning new technologies to enhance my expertise further.
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📫 How to reach me:janeyziqinglin@gmail.com
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📄 Know about my experiences(Resume)https://app.luminpdf.com/viewer/64b7683a2e8231f2cdc53026
- GitHub | Backend Website| Frontend Website
- Developed a Java full-stack shopping website using Spring Boot, Thymeleaf, Bootstrap, jQuery, and MySQL database.
- Built the Admin backend for users, products, customers, orders management using Spring Boot.
- Built role-based authentication and authorization using Spring Security to enforce access control based on user roles.
- Developed front end shopping cart features using HTML, JavaScript, Bootstrap, and jQuery, integrating PayPal Checkout API for seamless payment processing.
- GitHub back-end
- Designed a MERN stack (MongoDB, Express.js, React, Node.js) social media platform for content sharing.
- Built the backend using Node.js, Express, MongoDB to handle user registration, login, and friend-related operations.
- Add authentication and authorization using JSON Web Tokens (JWT) to restrict access to friend-related actions.
- Built a responsive front end homepage using React and incorporated React Dropzone for image uploads.
- GitHub front end
- Developed a MERN stack inventory management system for efficient inventory control and user profile management.
- Built the inventory backend using Node.js, Express, MongoDB, and implemented JWT-based authentication.
- Designed the React front end for state management and integrated a Cloud-based media management system.
- GitHub
- Developed an Android mobile app using Java and Kotlin, featuring efficient inventory control and offers management.
- Built intuitive user interface facilitating user-defined offer scoring, streamlined data entry, and edit capabilities.
- Designed a customizable job offer comparison feature, allowing users to compare offers with adjustable weights.
- GitHub
- Processed over 200,000 medical tumor dataset for image classification and achieved 90% accuracy
- Implemented data augmentation to increase the size of training dataset for improved model generalization using pandas and SciPy
- Built a detection model using Convolutional Neural Networks (CNN) and Graph Convolutional Neural Networks (GCNN) model using Tensorflow