Rashed Almarshedi
Computer Engineering Graduate - KSU | IoT & Embedded Systems | Backend & API
Innovative Computer Engineering graduate specializing in embedded systems, Internet of Things (IoT), and mechatronics. Passionate about developing intelligent hardware and designing resilient, connected systems.
About Me
Professional Summary
Innovative Computer Engineering graduate specializing in embedded systems, Internet of Things (IoT), and mechatronics. Passionate about developing intelligent hardware and designing resilient, connected systems. An agile problem-solver and collaborative team player, dedicated to continuous learning and engineering robust technological solutions for dynamic environments.
Tech Stack
Programming & Databases
- C++
- Python
- Java
- SQL
- InfluxDB
Frameworks & Libraries
- PyTorch
- Node-RED
- Convolutional Neural Networks (CNNs)
Tools & Technologies
- ESP32
- MQTT
- Grafana
- Linux
- Onshape
Projects
1. Automated Restocking Robotic System
An IoT-driven restocking system connecting smart retail shelves to a warehouse robotic arm.
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The Problem: Manual inventory monitoring causes restocking delays and stockout risks between retail floors and warehouse storage.
Tech Stack: C++, ESP32 (Dual Nodes), ESP-NOW, Ultrasonic Sensor, Servo Motors, LEDs.
My Role: Built a multi-tier replenishment system using ultrasonic sensors and ESP-NOW to trigger a servo robotic arm when stock drops below threshold levels.
2. IoT Telemetry Infrastructure
End-to-end secure IoT pipeline for real-time property monitoring and data visualization.
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The Problem: The requirement for real-time property monitoring through secure and centralized data pipelines.
Tech Stack: ESP32, MQTT, InfluxDB, Node-RED, Grafana.
My Role: Architected an end-to-end IoT telemetry infrastructure, integrating time-series data via InfluxDB and Node-RED and visualizing critical metrics on Grafana dashboards.
3. Computer-Aided Diagnosis (CAD) System
Deep learning system for automated diabetic retinopathy classification from retinal scans.
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The Problem: Enhancing early detection accuracy and supporting clinical ophthalmic diagnosis for diabetic retinopathy.
Tech Stack: Python, PyTorch, Deep Learning, CNNs.
My Role: Developed an advanced CAD system utilizing deep learning and retinal image analysis to automatically classify disease stages with high accuracy.
Education & Bootcamps
Bootcamp
Mechatronics Engineering Fundamentals Bootcamp
Tuwaiq Academy (July 2026)
Bachelor's Degree
Bachelor of Science in Computer Engineering
King Saud University (May 2026)
