Priyadharshini M
GoodProfile
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@priyadharshini-m-8a20232b7
About me
Computer Science undergraduate with hands-on experience in web development and academic projects, passionate about building user-focused applications and continuously enhancing technical skills.
Skills
Project
CivicLink
Civic Issue Reporting Platform • Developed a web-based civic issue reporting platform that enables users to report problems such as road damage, garbage accumulation, water leakage, and other local issues with image uploads and precise location tagging. • Implemented issue categorization and real-time status tracking, allowing users to monitor whether their reported complaints are pending, in progress, or resolved, improving transparency between citizens and authorities. • Ensured proper form validation and smooth user navigation for better usability.
Experience
Web Development Intern
Dec 2024 – Jan 2025Prodigy Infotech
- Developed responsive webpages using HTML, CSS, and JavaScript for real-world use cases.
- Improved UI usability and ensured seamless cross-device compatibility.
- Collaborated with team members to implement features and efficiently resolve UI issues.
- Completed assigned tasks within deadlines while adhering to project requirements.
Education
B.E.
Sep 2023 – May 2027St. Joseph's Institute of Technology · Computer Science and Engineering
Certifications
Meta Frontend Developer Certification
Networking and Web Technologies – Infosys
Database Management Systems – NPTEL
Data Structures and Algorithms using Java
Python for Data Science – NPTEL
AWS Cloud Associate Developer
Achievements
Solved 150+ coding problems on LeetCode, strengthening problem-solving and algorithmic thinking.
Solved 1000+ problems on Skillrack, improving logical reasoning and programming proficiency.
Actively participated in team-based coding and web development projects.
Member of CSI (Computer Society of India) – Kanchipuram Chapter.
Resume
Made on GoodProfile
Project
GlaucomaGuard
Multimodal Glaucoma Risk Prediction System • Developed an AI-based system that predicts glaucoma risk using retinal eye images and eye-blink videos. • Combined image and blink analysis using deep learning and computer vision to improve risk prediction compared with a single input. • Built an explainable Streamlit application with Grad-CAM visualization, allowing users to upload images/videos and view Low, Medium, or High risk results.
Project
Student Task Manager
- Created a task management application to organize and manage daily student activities.
- Implemented CRUD operations for efficient task creation, updating, and deletion.
- Improved productivity through priority-based task tracking and a responsive interface.