Building practical AI systems with a focus on Computer Vision, Deep Learning & Edge AI.
I’m a BS Artificial Intelligence student, AI engineer, researcher, and founder focused on turning AI research into practical, deployable systems.
- 🔬 Research: Computer Vision, Deep Learning, Edge AI, and intelligent surveillance
- 🚀 Building: PiLENS — an AI-powered surveillance and Edge Intelligence platform
- 🏢 Founder: PiVisen AI
- 🧠 Primary stack: Python, PyTorch, OpenCV, YOLO, Raspberry Pi
- 📄 Research goal: Developing publication-quality work around real-world Edge AI systems
- 🌍 Open to: AI research, engineering opportunities, collaborations, and internships
PiLENS: Raspberry Pi–Based Deep Learning Enhanced Nightvision Surveillance System is my primary research and product project.
The system combines real-time person detection, temporal activity analysis, night vision, and edge deployment to explore practical AI-powered surveillance on resource-constrained hardware.
Current research direction:
YOLO → Person Tracking → Temporal Action Model → Normal / Suspicious Activity
Edge models under evaluation: X3D · MoViNet
Cloud research direction: Video Swin Transformer · VideoMamba
Hardware: Raspberry Pi 5 · Camera Module 3 NoIR
| Project | What it demonstrates |
|---|---|
| PiLENS | Computer Vision · Deep Learning · Edge AI · Raspberry Pi · Intelligent Surveillance |
| MoodMate | Python · Speech/Voice AI · AI application development |
| AI Web Scraper Toolkit | Python · Web automation · Data extraction · Excel workflows |
| Python Course | Python fundamentals and learning progression |
I also work on AI automation, voice applications, computer vision pipelines, and applied machine learning systems, with an emphasis on building things that can move beyond notebooks into usable software.
Raspberry Pi · Edge AI · Computer Vision · Real-Time Inference · Model Optimization
- Computer Vision & Video Understanding
- Deep Learning for Real-World Applications
- Edge AI & Efficient Inference
- Intelligent Surveillance Systems
- Video Action Recognition
- AI Model Deployment on Resource-Constrained Devices
Research → Engineering → Product
My long-term goal is to build AI products that are technically strong, research-driven, and useful in real-world environments — starting with Edge AI and Computer Vision.
If you’re working on AI research, Computer Vision, Edge AI, intelligent systems, or applied machine learning, I’m open to meaningful technical collaboration.
Email · LinkedIn · GitHub · PiVisen AI