Hi, I’m

Yousef Hazza.

Computer Science & AI Graduate

I build intelligent solutions through artificial intelligence, machine learning, and thoughtful software development.

Abstract study of connected signals
View my projectsDownload CVContact me
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Based in Riyadh, Saudi Arabia

Connecting ideas. Building what’s next.

About me

Curiosity, put to work.

I’m a Computer Science graduate specializing in Artificial Intelligence, based in Riyadh. I’m interested in how thoughtful software and machine learning can turn complex questions into practical solutions.

My projects explore urban growth, review detection, and time-series forecasting. Alongside that work, an IT support internship taught me to test carefully, communicate clearly, and approach problems from the user’s perspective. I enjoy learning new tools and building with others.

My approach

Understand the problem. Explore the data. Build, test, and keep learning.

Selected projects

Ideas, tested in practice.

Exploring how data can help us understand places, language, and what comes next.

Majmaah, imagined forward

Land-cover study / CA–Markov
Move the slider to compare two synthetic land-cover scenarios.
Built environmentOpen land
Illustrative concept · not project output

Prediction of Majmaah 2030 Using CA-Markov

Predictive modeling · Geospatial analysis

Exploring how Majmaah may change by 2030 through historical land-use patterns and the Cellular Automata–Markov model.

  • Artificial Intelligence
  • Predictive Modeling
  • CA-Markov
  • GIS
  • Land Cover Change Analysis
Explore the project

Analyzes historical land-use and land-cover patterns in Majmaah, Saudi Arabia, to forecast urban growth and resource changes by 2030.

Uses the Cellular Automata–Markov model to examine how land-cover classes can change over time and across neighboring areas.

Supports analysis for sustainable planning and development in the context of Saudi Vision 2030.

The portfolio visualization is an illustrative explanation of the topic, not an actual project map or a validated forecast.

Reading between the lines

NLP / Streamlit
Example review
Perfect product! Best ever! Buy it now!
Text representation
TF–IDFSentimentBERT
Illustrative classificationPotentially deceptive

A concept for exploring review signals.

Illustrative concept · not project output

Fake Review Detection System

Natural language processing

An NLP system that brings text features and reviewer metadata together to identify potentially deceptive reviews.

  • NLP
  • TF-IDF
  • Sentiment Analysis
  • SVM
  • Random Forest
  • BERT
  • Streamlit
  • Classification Metrics
Explore the project

Combines TF-IDF and sentiment analysis with reviewer metadata to identify potentially deceptive product and service reviews.

Explores Support Vector Machines, Random Forest, and a fine-tuned BERT model for classification.

Includes a Streamlit demonstration for predictions and a notebook for experiments.

Evaluates classification using accuracy, precision, recall, and F1.

The interface shown in this portfolio is an illustrative concept, not a screenshot or a live model prediction.

Looking beyond the data

Time-series forecasting / model comparison
ARIMAProphetLSTM

Forecast horizon

Historical illustrationForecast illustration
Illustrative concept · not project output

Time-Series Forecasting Dashboard

Time series · Machine learning

A Streamlit dashboard for exploring stock price history and comparing statistical forecasts with deep learning models.

  • Python
  • Streamlit
  • ARIMA
  • Prophet
  • LSTM
  • Plotly
  • Alpha Vantage
Explore the project

Fetches historical stock price data from Alpha Vantage and visualizes trends with Plotly.

Integrates ARIMA, Prophet, and LSTM to compare classical statistical and deep learning approaches to time-series forecasting.

Provides interactive charts, stock symbol selection, adjustable forecasting horizons, and model selection in a Streamlit interface.

The portfolio chart uses illustrative data to explain the project rather than live market data or actual model results.

Experience

Learning in the real world.

Practical experience supporting the people and systems that keep a hospital working.

June — August 2023

Al Majma’ah, Saudi Arabia

IT Technical Support Intern

King Khaled Hospital

  • Tested new systems before implementation, contributing to a reported 10% reduction in incidents.
  • Installed and updated software to support system security and reliability.
  • Helped nontechnical employees through training sessions and clear, practical IT support.
  • Supported daily IT operations and troubleshot hardware and software issues to help maintain a reliable working environment.

Skills

A toolkit for possibility.

Foundations I bring to a project, and keep developing with each new challenge.

Artificial Intelligence

  • Machine Learning
  • Artificial Intelligence
  • Data Structures & Algorithms

Software Development & Quality

  • Agile Methodology
  • User Acceptance Testing
  • Software Development Foundations

Working Together

  • Critical Thinking
  • Team Collaboration
  • Attention to Detail
  • Time Management
  • Problem-Solving

Education

A foundation to build on.

2024

Bachelor of Computer Science

Artificial Intelligence

Majmaah University

Al Majma’ah, Saudi Arabia

Graduated: January 2024

Continued learning

  • Artificial Intelligence Fundamentals

    IBM

  • Natural Language Processing with Classification and Vector Spaces

    Coursera

  • Software Engineering: Modeling Software Systems Using UML

    Coursera

  • Supervised Machine Learning: Regression and Classification

    Coursera

Let’s build something great.

Have a project in mind or an opportunity to share? I’d love to hear from you.

yousefhazza0@gmail.com
Send an email
LinkedInDownload CV