Programming

Most of my work involves embedded systems, algorithm development, and signal processing. I use C/C++, Python, Matlab and VHDL for simulation, modelling, firmware, and hardware verification.

You’ll find examples of:

• Embedded firmware for PIC, AVR and ARM microcontrollers.
• FPGA modules and verification testbenches.
• Signal‑processing scripts in Python and Matlab.
• Reproducible GNU/Linux workflows and tooling.
• Small utilities and experiments.

I keep the examples practical and minimal.

Access to code
Where possible I link to repositories on GitHub. If a project is not public, please check GitHub first or contact me and I can provide access or a curated excerpt on request.

Indicative Projects

I am adding short project summaries and links here:

FPGA‑Based Spread Spectrum — Configurable maximum‑length sequences at line rates up to 10 Gb/s.

• Tech: FPGA; MATLAB; PCB design; optical transceivers
• Status: Prototype / FPGA demo
• Notes: The FPGA generates and transmits maximum‑length sequences to modulate an optical transceiver at line rates up to 10 Gb/s. Includes test vectors and timing analysis.

FFTW3 Projects — High‑performance FFT projects using FFTW3.

• Tech: C / C++
• Status: Library integrations / Benchmarks
• Notes: Optimized implementations for spectral analysis, filtering, and real‑time signal processing; includes benchmark scripts and example pipelines.

LSTM Prediction Code — Sequence and time‑series prediction for multiple domains.

• Tech: Python; TensorFlow / PyTorch examples
• Status: Reusable modules / Examples
• Notes: Modular training and inference code with examples for forecasting, anomaly detection, and sequence classification.

AI Assistant v8.8.0 — A production‑grade assistant with enhanced TTS, refined UI, and Docker deployment.

• Tech: React; GenAI; Docker
• Status: Stable release (v8.8.0)
• Notes:
  • Google Neural TTS: Native support for Google’s neural voices via the Gemini API. Ensure GEMINI_API_KEY is configured.
  • Ollama support: Seamless integration with local Ollama models for on‑device inference.
  • Model Support: Supports Gemini 3.5 Flash, Gemini 3.1 Flash Lite, and Imagen 3.
  • Storage: Migrated from localStorage to IndexedDB for robust, larger‑scale storage.
  • UI: Immersive, professional interfaces with glassmorphism, animated backgrounds, and high‑quality typography.

Raspberry Pi Pico Projects — Embedded projects using the Pico and TFT displays.

• Tech: Raspberry Pi Pico; MicroPython / C; TFT displays
• Status: Prototypes / Demos
• Notes: Examples for embedded UI, sensor integration, and display drivers.

More to come — stay tuned
This list is indicative and will be expanded with links, demos, code samples, and status updates.

Check back soon for detailed project pages, repository links, and short walkthroughs.