ISSAM SAYYAF
Embedded Systems Engineer · PhD Researcher
Summary
Embedded Systems Engineer with 4+ years of experience bringing products to life — from custom Linux BSPs (Yocto/Buildroot) and device drivers to RTOS-based real-time systems on STM32MP1 and NXP i.MX platforms. Currently completing a PhD in signal processing and deep learning for navigation systems, with 8+ peer-reviewed publications. Passionate about bridging R&D innovation with reliable, production-ready embedded solutions across automotive, IoT, and sensor-fusion domains.
Professional Experience
- Built 3+ custom Linux images with Yocto/OpenEmbedded for STM32MP157 and NXP i.MX93 platforms, including U-Boot, kernel configuration, and root filesystem customization
- Developed 10+ Linux device drivers (GPIO, I2C, SPI, UART, LoRaWAN, Zigbee, BLE) and integrated them into BSP layers with device-tree overlays
- Designed embedded C++ application orchestrating IMU, audio codec, BLE, Wi-Fi, and battery management for the Muzziball product, interfacing with Pure Data for real-time audio processing
- Implemented CAN bus, 5G modem, and GNSS drivers for NXP i.MX93-based truck monitoring system
- Developed deep learning anomaly detection algorithms for IMU, GNSS, and 5G sensor fusion in real-time navigation
- Improved pedestrian step detection accuracy by 23% using unsupervised anomaly filtering on 10,000+ samples across 5 environments
- Analyzed 800+ min of GNSS signal data, identifying jamming and spoofing patterns for integrity monitoring
- Designed autoencoder-based LOS/NLOS classification for 5G indoor positioning using CIR feature extraction
- Designed distributed sensor measurement systems for structural health monitoring using LabVIEW and Python
- Built wireless IoT crack detection system (hardware, firmware, cloud dashboard) for heritage buildings
- Led 50+ lab sessions for 150+ students in antenna design (HFSS/CST), microwave engineering, and RF systems
Key Projects
Custom Yocto image for STM32MP157 integrating IMU, audio, BLE, Wi-Fi, and charging subsystem. Full BSP, device drivers, and embedded C++ application for real-time sensor data acquisition and audio processing.
Custom Linux BSP for vehicle fleet tracking. Developed drivers for 5G modem, GNSS receiver, IMU, and CAN bus. Integrated connectivity stack and OTA update mechanism.
Lightweight deep learning anomaly detection for pedestrian dead reckoning using IMU data. 23% accuracy improvement, optimized for embedded deployment. Published at IEEE/ION PLANS 2025 and IEEE APSCON 2025.
End-to-end IoT system: acoustic emission sensor hardware, STM32 firmware, wireless communication, and cloud dashboard. Published at IEEE MetroLivEnv 2023.