Ayoob Al-Delaimy - Portfolio

About Me

I'm a Computer Engineering student at UC San Diego, expected to graduate in June 2026. With a strong foundation in both software and hardware, I'm passionate about creating innovative solutions that bridge the gap between technology and real-world applications.

Education

University of California, San Diego

B.S. Computer Engineering (Expected June 2026)

Relevant Coursework:

Design and Analysis of Algorithms
Data Structures (C++)
Computer Architecture (C/Assembly)
Object-Oriented Programming (Java)

Technical Skills

Python
JavaScript/TypeScript
React/React Native
Node.js
Express
Git
C++
C
Arduino
Assembly

Professional Experience

Founding Engineer & CEO

FiNDi

Jan 2025 - Present

Founding a cross-border e-commerce platform enabling international customers to shop U.S. marketplaces
Designing and developing platform architecture using React, Node.js, Express, and SQL
Managing logistics strategy and carrier partnerships
Leading development phase with planned launch in June 2025

Software Engineer Intern

San Diego Supercomputer Center

Nov 2023 - Jan 2025

Developed comprehensive web app for Research Data Services (RDS) division
Delivered front-end and back-end pages using React, JavaScript/TypeScript, HTML, and CSS
Adapted to fast-paced environment and met tight deadlines
Resolved technical challenges through research and collaboration

Embedded Systems Intern

UC San Diego

Jan 2021 - Jan 2022

Designed and programmed robotic arm for Nanoengineering research group
Independently managed hardware design and software programming
Created innovative non-sensor-based solution using mathematical equations
Solution featured in research paper for efficiency and precision enhancements

Projects

Smart Wardrobe Management System

IoT-Powered Intelligent Clothing Selection System

Led the development of an IoT-powered wardrobe management system, enabling real-time environmental monitoring for intelligent clothing selection.
Designed and implemented a full-stack solution integrating ESP32 sensors, MQTT, FastAPI, MySQL, and Docker, with external weather API support.
Developed a secure web interface with real-time data visualization and smart clothing recommendations, serving multiple users.
Enhanced system scalability and efficiency, implementing edge computing on ESP32 for pre-processed sensor data and optimizing cloud workload distribution.

ESP32 FastAPI MQTT MySQL Docker

GitHub

DALL·E Image Generation Platform

AI-Powered Image Generation & Sharing Community

Built a full-stack web application using the MERN stack (MongoDB, Express, React, Node.js) to generate and share AI-generated images.
Integrated OpenAI's API to allow users to input a script, generate images, and share them with the community, with the ability to search for shared images.

MongoDB Express React Node.js OpenAI API

Live Demo GitHub

MNIST Digit Classification System

Deep Learning System for Handwritten Digit Recognition

Developed a deep learning system achieving 98% accuracy on the MNIST dataset by optimizing the training pipeline, reducing training time by 40%.
Implemented a robust testing and validation framework with automated pipelines and visualization tools, ensuring deployment-ready performance.
Engineered an efficient custom data loading and preprocessing system, reducing computational overhead by 40% while maintaining high accuracy.
Optimized model architecture by fine-tuning hyperparameters and leveraging convolutional neural networks (CNNs), improving both training efficiency and generalization.

Python PyTorch Deep Learning Computer Vision