I enjoy building embedded systems from the ground up. Most of my work involves firmware development, hardware-software integration, and experimentation with system-level programming. I'm also curious about how AI and automation can be applied in edge computing, signal processing, and real-world decision-making.
This GitHub is a collection of personal experiments, course projects, and professional tools I've developed over the years.
- 🧠 AI & Data Science: PINNs, reinforcement learning, model tracking, and edge ML.
- ⚙️ Embedded Systems: STM32, ESP32, nRF52, bare-metal programming, RTOS, Zephyr.
- 🧪 Testing & CI: Ceedling, Docker, Jenkins, data pipelines, TDD.
- 🧰 Toolchains: Yocto, Linux kernel modules, Buildroot, QEMU.
- 📡 Connectivity: BLE, MQTT, LoRa, SBUS, I2C/SPI abstraction.
- 📊 Visualization & Analysis: Data loggers, sensors, dashboards, stream processing.
- 📚 Learning Projects: FPGA, VHDL/Verilog, operating systems, Python scripting.
- Yocto BSP & kernel modules — YOCTO, IMD
- STM32 RTOS + OS experiments — test-stm32-os, STM32F4-BARE-METAL
- Peripheral drivers (I2C, SPI, GPIO expanders) — port_spi, mcp23s17
- Physics-Informed Neural Networks (PINNs) — IA-PINN
- Reinforcement learning for finance — stock-trading-DQL
- NLP experiments — NLP
- ML service comparison — ml_services_comparison
- TDD with Ceedling — TDD-MOCK, TDD-LED
- Valgrind in Docker — Valgrind
- Build systems & automation — Test-makefile, zephyr-docker
🕒 I work on these projects during my free time and use GitHub to document, learn, and share.