Ahmad Masarrat

Developed and debugged STM32/ESP32 embedded systems using C, interrupts, HAL, UART, I2C, SPI, and register-level peripheral configuration. Built NEO firmware for a 7-subsystem custom CubeSat kit end to end, and reviewed and developed CubeSat OBC, communications, payload, and power PCBs.

Promoted from Communication Systems Engineer to Payload Lead, leading development of a 1U CubeSat LoRa wildlife-tracking payload operating at 437 MHz. Engineered Raw LoRa communications, GNSS-based Doppler compensation, LDRO algorithms, TDD interference control, and authenticated low-overhead packet structures.

R&D for AI products, covering model selection, experimentation, validation, and technical feasibility for startup use cases. Developed drone-based computer-vision solutions for inspection, object detection, and classification, with focus on deploying models within small-form-factor payload and edge-computing constraints.

R&D of a real-time computer vision system for sign-language recognition to support deaf and hard-of-hearing users in public institutions. Built a synthetic-data generation pipeline using GANs to address severe dataset scarcity and improve training diversity.

Designed and simulated electrical systems using KiCad, Fusion 360, and EasyEDA. Developed Simscape models and PCB blueprints for high-accuracy electrical designs, and conducted thermal and power dissipation analysis.

Researching Dual Heterogeneity in Over-the-Air Federated Learning: Convergence Analysis and Gradient-Importance-Aware Scheduling. Completed a review study on satellite networks and prepared research papers in IEEE format using LaTeX and Overleaf.

Pursuing a Bachelor of Science in Communication Systems Engineering.