Skip to main content May 2024 - now May 2024 - now obscuRRRa Offline desktop app for privacy-focused batch face blurring AI/ML ›
- Built Python face blurring app using MTCNN model achieving 96.4% accuracy on 10,000-image dataset
- Enabled batch processing for large-scale face detection and anonymization in local environment
- Developed an offline-capable (GUI) graphic user interface with Tkinter to ensure privacy and usability and released on GitHub
Jan 2025 - May 2026 Jan 2025 - May 2026 Undergraduate Researcher McComish Dept of Electrical Engineering and Computer Science, SDSU AI/ML ›
- Awarded $5,000 Future Innovators grant to develop AMBER: Python-based real-time hazard detection system with edge computing
- Researching sensor fusion and ML-based risk assessment models using Python, OpenCV for hardware prototyping and testing
- Investigating low-latency risk detection integrating Raspberry Pi 5 edge devices with multimodal sensor fusion