Learn more about my technical journey and what drives my work in engineering and AI.
I'm a hands-on engineer with experience spanning embedded systems, signal processing, and machine learning. My work bridges physical devices and intelligent software.
Over the years, I’ve designed IoT testbeds, deployed real-time analytics pipelines, and built predictive models for applications in manufacturing, healthcare, non-destructive testing (NDT), acoustics, and signal processing.
I enjoy creating focused, practical solutions—from sensor integration to full-stack ML applications.
Ph.D. in Signal Processing with a focus on real-world data from sensors, acoustic systems, and industrial environments.
My expertise spans the full stack of intelligent system development—from low-level sensor integration and firmware development to signal processing, predictive modeling, and cloud-based deployment.
I work with Python, C/C++/C#, Go, Rust, Azure/GCP/AWS cloud platforms, and modern web frameworks, integrating tools like NumPy, SciPy, scikit-learn, TensorFlow, and FastAPI to solve applied problems in machine learning and signal processing.
I also enjoy using LaTeX to produce clean, professional technical documentation, including articles, presentations, and structured diagrams.