Real engineering projects
You don't just study concepts, you build real systems. From AI models to embedded hardware and interactive simulations, your project is designed to function, not just exist on paper.
Build systems, not just research papers.
AeduLab · Engineering program
Build real engineering systems.
AeduLab is an elite engineering program where ambitious high school students design, build, and deploy real AI, robotics, and XR systems with personalized mentorship.
- AI
- Robotics
- XR
Why AeduLab
What you gain from AeduLab
- 01
Build real AI, hardware, and systems, not just theory
- 02
Stand out in top university applications with real project outcomes
- 03
Graduate with a working system, demo video, and portfolio-ready project
Mentorship like a real lab
Work with experienced mentors who guide you through:
- System design
- Debugging and iteration
- Integration and testing
Your project evolves the same way real engineering projects do, step by step. Not teaching. Real project guidance.
A portfolio that stands out
By the end of the program, you will have:
- A working system
- A demo video
- A GitHub repository
Proof of ability, not just claims.
Built for your ambition
Your project is tailored to your goals:
- University applications
- Engineering interests
- Skill level
Go deeper, build stronger.
Project track · AI-Powered VR Interactive System
Most students build projects. You control virtual worlds.
Build an AI-powered system that interacts with a virtual environment in real time. Create a complete system where AI recognizes your input and controls a virtual world.
Design how humans interact with machines, not just use them.
What you will build
- Computer Vision (gesture recognition)
- AI model integration
- Real-time interaction design
- VR / XR system development
What you will leave with
- An interactive VR system
- A demo video
- A GitHub project
- Interactive VR System
- Demo Video
- GitHub Project
This is not a course. This is a real interactive system.
Apply for this project · Only 20 students
Project track · AI + Embedded Intelligent Control System
Build intelligence into real hardware.
Create a complete system that connects AI recognition, control logic, and embedded devices in real time.
This project is for students who want to go beyond software and build a real engineering system. You will combine AI, control logic, and embedded hardware to create a system that reacts to human input and produces visible real-world output.
System flow · live
- 01
Human input
Gesture, voice or sensor signal
- 02
AI recognition
Model classifies the input
- 03
Control logic
Real-time decision rules
- 04
Embedded device
Microcontroller drives actuators
- 05
Visible output
Lights, motion, display
What you will build
- Recognize inputs using AI
- Process signals with real-time logic
- Control embedded hardware dynamically
- Generate visible feedback through displays or devices
What you will leave with
- A working intelligent control system
- A demo video
- Complete project documentation
- A GitHub repository
- Intelligent Control System
- Demo Video
- Documentation
- GitHub Repository
This is not just coding. This is a real intelligent system.
Apply for this project · Only 20 students
Project track · AI Vision + Robotics Control System
Build a system where AI sees, decides, and controls.
Create an intelligent system that uses computer vision to recognize the world and guide robotic actions in real time.
This project is designed for students who want to explore how AI and robotics work together in real systems.
You will build a system where AI vision detects objects, interprets input, and sends instructions to a robotic or controlled device.
System flow · live
- 01
Camera
Live video input
- 02
AI vision
Detect objects, positions, motion
- 03
Decision
Plan the next action
- 04
Robot action
Arm or device executes
What you will build
- Recognize objects, positions, motion using AI vision
- Process visual information with real-time logic
- Send commands to a robotic or control system
- Make the system perform visible actions based on AI decisions
Skills you will gain
- Computer vision fundamentals
- AI vision model
- Control logic layer
- Robotic system integration
- Vision-to-action pipeline design
Key components
- Camera or vision input module
- AI-based object recognition
- Robotics control logic
- Real-time system integration
What you will leave with
- A working AI vision + robotics control system
- A demo video (portfolio ready)
- Complete project documentation
- GitHub repository
- Vision + Robotics System
- Portfolio Demo Video
- Documentation
- GitHub Repository
This is not just AI analysis. This is AI driving action.
Apply for this project · Only 20 students