Welcome to my GitHub! I'm a Computer Engineering M.S. graduate (GPA 4.0, ARCS Fellow) working at the intersection of embedded systems, machine learning, and hardware–software co-design — with peer-reviewed publications in edge ML and distributed learning. Currently seeking full-time roles in embedded AI, ML engineering, or software engineering.

• 🎓 Education
  • M.S. Computer Engineering, CSUN — GPA 4.0/4.0, ARCS Fellow — Graduated May 2026. Thesis: Hardware-Accelerated Deep Learning for Multimodal Biomedical Monitoring with On-Device Adaptive Learning (advisor: Dr. Shahnam Mirzaei) — patent pending.
  • B.S. Computer Engineering, CSUN — GPA 3.94/4.0, Summa Cum Laude — Graduated May 2024.
• 🏆 Highlights: Best Paper Award, IEEE ICHI 2026 · Distinguished Thesis Award, CSUN (university-wide, 1 of 4 selected from 18 theses across 9 colleges) · Outstanding Graduate Student Award, ECE Dept. · 1st Place, CSUNposium Research Competition · Nominated as Commencement Speaker, College of Engineering & CS.
• 💼 Experience: Graduate Research Assistant & Research Assistant (ARCS Program and MOSAIC Lab) at CSUN · AI/ML Engineer Intern at PM Accelerator · Data Analyst Intern at ConXtech · Teaching Assistant at CSUN · Data Analyst at Unipal · Peer Tutor & IT Technician at AUBH.
• 🚁 Presented "Mars Helicopter – Backup System" research at NASA's Armstrong Flight Research Center (2025).
• 🏅 Memberships: ARCS Foundation Fellow, IEEE-Eta Kappa Nu (IEEE-HKN), The Honor Society of Phi Kappa Phi.
• 🌍 Languages: English (Fluent), Arabic (Native), Korean (Conversational).

• Languages: Python, C++, C, Java, MATLAB, VHDL, Verilog, SystemVerilog, HTML, CSS
• ML & AI: PyTorch, Deep Learning, TinyML, Edge AI, Model Optimization, Distributed Machine Learning, Feature Engineering
• Embedded & Hardware: ESP32, Jetson, Raspberry Pi, SEEED XIAO nRF52840, ARM Microcontrollers, FPGA, SoC Design, I2C, SPI, UART, PlatformIO, Arduino
• Software & Cloud: React, Django, REST APIs, PostgreSQL, MySQL, AWS RDS, Kubernetes, Power BI
• Tools: Git, Bash, Azure DevOps, JIRA, Confluence, Vivado, Multisim, PSpice, Figma

🏆 Best Paper Award, IEEE Int'l Conf. on Healthcare Informatics (ICHI) 2026, for my thesis work on edge deep learning for biomedical monitoring.

1. S. Aly and S. Mirzaei, "Hardware-Aware Edge Deep Learning for Multimodal Biomedical Monitoring on Resource-Constrained SoCs," IEEE Int'l Conf. on Healthcare Informatics (ICHI), 2026. 🏆 Best Paper Award
2. M. Cho, S. Ali, et al., "Distributed Dual Coordinate Ascent in a Ring Network for Distributed Machine Learning," Proc. Asilomar Conf. on Signals, Systems & Computers, 2025.
3. P.L. Bishay et al., "The Foot Can Do It: Controlling the 'Persistence' Prosthetic Arm Using the 'Infinity-2' Foot Controller," Technologies, 13(3), 98, 2025. DOI
4. S.K. Abdelhakeem, Z.M. Mustafa, H. Kadhem, "Diagnosing Parkinson's Disease Based on Voice Recordings: Comparative Study Using Machine Learning Techniques," Proc. AIVR 2022, Springer Nature, 2023. DOI

Patent Pending · C++ / Python · ESP32-S3

• Multi-task CNN-SE-Transformer running entirely on-device for real-time ECG arrhythmia, stress, and activity classification — no cloud dependency.
• On-device adaptive learning via head-only backpropagation (4,984 trainable vs. 107,568 frozen params) → 715× reduction in activation storage over full backprop.
• Persists personalized weights to NVS flash across reboots within 300 KB heap / 8 MB PSRAM.
• 297 ms inference latency on 10-second multi-sensor windows (ECG, PPG, IMU, GSR).

• Integrated a Bluetooth-enabled foot controller with a biomechanical prosthetic arm prototype via embedded C++ firmware.
• Built the wireless communication stack between controller and arm hardware — max transmission delay under 165 ms.
• Published in Technologies, vol. 13, no. 3, MDPI, 2025.

🏆 Best Paper Award, IEEE ICHI 2026 · 🎓 Distinguished Thesis Award, CSUN (1 of 4 selected from 18 theses across 9 colleges) · 💰 ARCS Fellowship · ⭐ Outstanding Graduate Student Award, ECE Dept. · 🥇 1st Place, CSUNposium Research Competition