Dlayel Aluhaideb

I'm an Artificial intelligence fresh graduate from Imam Abdulrahman bin Faisal University. Interested in machine learning and computer vision, I'm on the lookout for Cooperative Training opportunities to grow and tackle new challenges. Eager for hands-on experiences to refine my skills and contribute to AI advancements.

• ITILv4
• UiPath Certified Professional Specialized AI Professional
• Deep Learning Crash Code

• An Honor Student (GPA over 4.5)
• AI Student representative at the ABET meeting for 2023
• Over 500 hours of volunteering work

Stuttering Disfluency Detection and Correction Using Artificial Intelligence (Senior Project) 

• This project focuses on individuals who stutter as well as those experiencing speech disfluencies.
• This project processes the stuttered speech by implementing multiple Large Language Models that support the Arabic language and return a stuttered-free text and speech.
• The Whisper AI library was used for preprocessing the stuttered speech.
• The Flutter software was used in building the application.
• This project stood out among more than 1500 submissions and advanced as one of the 20 projects that got nominated to the final round of the "Tamkeenthon" hackathon, organized by the Authority for the Care of Persons with Disabilities.

E-mail Classification using Recurrent Neural Networks and Natural Language Processing

• This project proposes an E-mail classification approach using NLP and Deep Learning techniques.
• The algorithms used to deploy the deep learning model were the Bidirectional Gated Recurrent Unit (BiGRU) and Bidirectional Long-Short Term Memory (BiLSTM).
• The word2vec method was used as the word embedding technique in the data preprocessing phase.
• The Accuracy achieved by the BiLSTM model was 85.24% while the BiGRU model achieved 83.61%.
• Role: Leader

Water Quality Prediction using Artificial Intelligence Algorithms

• This project proposes a predictive model using machine learning algorithms (SVM, Decision Tree, KNN) to asses water potability.
• The SMOTE technique was Implemented as the data preprocessing technique to deal with dataset imbalance while the Stratified Cross-Validation was implemented for hyperparameter tuning.
• The utilized feature extraction technique was the Sequential Feature Selection.
• The Ensemble technique was employed to enhance the model's generalization.
• The highest Accuracy was achieved by the Decision Tree as 73.75%.

Measuring the Size of an Object using Image Processing Technique

• This project preprocesses images and applies preprocessing techniques to automate the process of measuring object sizes.
• The Blurring, Canny Edge Detection and Contour Calculation techniques were utilized to accurately identify object boundaries.
• The Euclidean Function was used to calculate distances between points within objects and lastly converted pixel measurements to centimeters.
• The Error Rate achieved by the model was 6.15%.

Exhibition of Academic Majors by Mostaqbli (2023)

Representative of The AI Major

TELE at IAU (2023)

Speaker at The " Fundamentals of ITILv4" Workshop

"Qoot" Campaign (2023)

Volunteering Organizer

Google Developer Student Club at IAU (2022)

Vice-Head of the Publication Unit

Robothink Educational Center (2022)

Volunteering Trainer

Alsharqiya Gets Creative Exhibition (2022)

Representative of The Artificial Coloring Booth

Imam Abdalrahman bin Faisal COVID-19 Vaccination Center (2021)

National Vaccination Register Volunteer (NVR)