I'm a Biomedical Signal and Imaging Engineer working at the intersection of signal processing, computational imaging, and scientific computing.
My work focuses on transforming complex biomedical signals and imaging data into reliable computational pipelines for image reconstruction, quantitative analysis, and system prototyping. I build and deploy end-to-end processing systems that convert raw measurements into interpretable and robust outputs for research and real-world applications.
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Spectral-Domain OCT 3D Pipeline
Advanced reconstruction image and signal processing pipeline, including FFT, dispersion compensation, and volume processing
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Digital PLL – I/Q Phase Detector
Visual and mathematical exploration of digital PLL, NCO, and phase convergence analysis
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Kalman Filter Actuator Simulation
State estimation, system modeling, and simulation
🔹 Biomedical Signal Clustering
Pattern extraction, clustering, and feature analysis
🔹 Numerical interpolation & transformation modeling experiments
🔹 Reinforcement Learning – Biped Robot Control
🔹 LLM-based Sentiment Analysis
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CNN-based Image Processing Experiments
Deep learning CNN framework in PyTorch for monocular depth estimation with metric-scale mapping.
- CUDA-accelerated signal processing kernels
- Memory-optimized FFT workflows
- Large-scale 3D biomedical volume handling
Core Skills
- Signal & image processing
- Fourier and wavelet analysis
- Numerical algorithms
- Data analysis & visualization
Tools
- NumPy, SciPy, PyTorch
- MATLAB toolboxes
- Git, Jupyter
- High-performance signal processing
- Research-to-production translation
- Applied ML for biomedical and sensing systems
- 💼 LinkedIn: https://www.linkedin.com/in/arman-rajaei/
- 📧 Email: arman.rajaei1992@gmail.com
