Analytics
Github Contributions
Project Commits
Personal Repository
New Project Direction
Facial Recognition Software
- Built a facial recognition system using a deepface-based neural network to match a user’s live image against their stored profile photo for identity verification.
- Implemented backend image handling with Base64 encoding, where the initial profile image from the profile page is encoded and securely stored for later recognition.
- Designed the system for bathroom check-in and check-out efficiency, while also logging timestamps to measure usage time for analytics in the spring.
Contributions History
Database Guys:
- Created an Admin Table
- Designed and implemented an administrative table interface
- Student Data Integration
- Displays student name, class, and grade
- Structured data for easy viewing and management
- Backend Mapping
- Mapped functionality from Flask to Spring
- Ensured consistent behavior across backend frameworks
- Mood Analysis API
- Developed a mood detection API using a Deep Face neural network
- Captures user images and analyzes emotional state
- Data Encoding & Transfer
- Utilized Base64 encoding and decoding for image handling
- Implemented secure POST and GET request workflows
- Frontend Integration
- Integrated the API into the user profile page
- Enabled real-time mood analysis from captured images
Pirna
- S3 Bucket File Setup
- Implemented a group-based folder structure in S3 during the spring
- Organized message files by group to ensure clean data separation
- Backend Evaluation & Integration
- Evaluated existing backend and S3 configuration
- Identified and implemented group-scoped API endpoints
- Ensured backend logic aligns with the S3 file structure
- Structured Message Storage
- Standardized message data using a consistent schema
- Includes name, message, ISO-8601 timestamp, and base64-encoded image
- Designed to support future scaling and analytics
Overall Java Conceptual Understanding
| AP CSA Unit | How it was used |
|---|---|
| Unit 4: Iteration (Loops) | Process image data and API responses during mood analysis |
| Unit 5: Writing Classes | Define API handlers and data-processing logic for mood detection |
| Unit 6: Arrays | Store and manipulate encoded image data and response values |
| Unit 7: ArrayLists | Manage collections of mood results or user submissions dynamically |
| Unit 4: Iteration (Loops) | Iterate through user records to dynamically populate the admin table |
| Unit 5: Writing Classes | Define user models and backend logic for Spring database integration |
| Unit 6: Arrays | Store and process multiple user records retrieved from the database |
| Unit 7: ArrayLists | Manage dynamic collections of users for admin-side operations |
FRQ Completion
| FRQ 2025 Q2 | 2024 Q2 | 2024 Q1 | 2016 Q3 | 2019 Q4 |
MCQ Completion
