MEng in Electrical and Computer Engineering

Technical University of Crete, Chania, 2014-2021

Freelance Software Engineer

10/2024-Present

• Manage end-to-end embedded projects from proposal to delivery, developing custom firmware and drivers for ESP32 and STM32 platforms while providing comprehensive documentation, integration guidance, and debugging support to clients.
• Expanded skill set into web development, successfully delivering website development contracts.

Machine Learning Research Assistant

MHL, Technical University of Crete, 2/2021-8/2024

• Designed and implemented complete CNN training and inference pipeline from scratch in C, optimizing for FPGA acceleration on Zynq UltraScale+ MPSoC. Achieved 1.5x speedup over CPUs and 7.8x GPU and 16.55x CPU energy efficiency
• Leveraged GEMM operations, He-Initialization, and LeakyReLU to maximize performance, showcasing detailed understanding of neural network math for FPGA-based solutions
• Submitted work on FPGA-optimized, energy-efficient CNN acceleration in IEEE Transactions on Circuits and Systems I.

Embedded Software Engineer

Cicicom Ltd, 7/2022-11/2023

• Integrated radar into Gen 2 parking spot sensor, improving accuracy from 91% to nearly 100% and optimizing battery life; comparison with Bosch and Fleximodo equivalents demonstrated higher accuracy.
• Utilized STM32 MCU ecosystem on a PCB with I2C, SPI, and UART communications, featuring BLE, electromagnetic, and LoRaWan / NBIOT communication modules.
• Streamlined verification and setup firmware for parking sensor PCB, reducing process time from 5 to 1 minute, significantly saving factory production time and reducing associated costs.
• Developed a GUI application for SSH communication with Raspberry Pi to automate PCB flashing and testing, accelerating the assembly line process.
• Contributed to Gen 3 PCB development, adding new features and improving component selection.
• Established DevOps pipelines with Jenkins and SonarCloud, enhancing workflow and code quality.
• Developed a LoRaWAN data analytics tool using Pandas, NumPy, and Matplotlib, processing over 1 million payloads from 300+ sensors. This tool was instrumental in securing a major project by identifying critical issues and is now a cornerstone in the company’s monitoring process for all new projects, ensuring ongoing success and reliability.
• Led R&D efforts on an innovative fire prevention solution utilizing the BME688 AI-based gas sensor ("digital nose"), conducting feasibility studies and prototype development to explore new market opportunities.
• Mentored junior engineer through structured guidance and problem-solving techniques, facilitating their understanding of the company’s tech stack while fostering independent critical thinking and solution development skills.
• Led testing for Gen 2 sensor, creating scripts for automated data processing and boosting productivity.

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