I build intelligent systems at the intersection of artificial intelligence, computer vision, computational biology, and efficient computing.
My work focuses on developing reproducible AI solutions, from deep learning models and scientific experiments to low-level systems and hardware-aware implementations.
I am a Computer Engineering graduate from Babol Noshirvani University of Technology with a growing focus on AI research and engineering.
My interests include:
- 🧠 Deep Learning and Artificial Intelligence
- 👁️ Computer Vision and Image Understanding
- 🧬 Bioinformatics and Computational Biology
- 🔗 Graph Neural Networks
- ⚡ Efficient AI Systems and Computer Architecture
I enjoy building complete research and engineering projects — including implementation, experimentation, evaluation, visualization, and documentation.
Artificial Intelligence
Deep Learning · CNNs · Graph Neural Networks · Model Evaluation
Computer Vision
Image Processing · OCR · Representation Learning · Vision Systems
Bioinformatics
Protein Analysis · Biological Data · Computational Modeling
Systems Engineering
C Programming · POSIX · Networking · Performance-oriented Software
Hardware & DSP
VHDL · FPGA Concepts · Digital Signal Processing
| Project | Description | Technologies |
|---|---|---|
| Protein Interface GNN | Research-oriented graph neural network framework for protein interface prediction | Python · PyTorch · GNN · ESM-2 |
| Persian OCR Engine | Deep learning based OCR system focused on Persian document understanding | Python · PyTorch · Computer Vision |
| StegaVision Toolkit | Computer vision toolkit for image analysis and information processing | Python · OpenCV |
| ComputerVision DSP Toolkit | Computer vision and digital signal processing implementations | Python · OpenCV · DSP |
| POSIX HTTP Server | Low-level HTTP server using sockets, processes, and IPC | C · POSIX · Networking |
| VHDL Audio Signal Processor | Hardware-oriented audio processing pipeline | VHDL · DSP · Python |
- Advanced Deep Learning architectures
- Graph Neural Networks for biological applications
- Computer Vision research
- Large-scale AI experimentation
- Efficient model design and deployment
Build intelligent systems.
Understand the fundamentals.
Experiment scientifically.
Write clean and reproducible code.
Share knowledge through documentation.
Explore all repositories:
https://github.com/masihBeykaei