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🎓 Education

Master of Science (M.Sc.) – Artificial Intelligence and Data Science
Heinrich Heine University Düsseldorf, Germany
10/2023 – Present
https://www.hhu.de/

Bachelor of Science (B.Sc.) – Computer Science
King Fahd University of Petroleum & Minerals, Saudi Arabia
09/2018 – 06/2023
GPA: 3.94 / 4.00
Concentration: Artificial Intelligence & Machine Learning

Key Courses:

  • Deep Learning
  • Machine Learning
  • Natural Language Processing
  • Computer Vision

https://www.kfupm.edu.sa/

💼 Work Experience

Undergraduate Research Assistant

SDAIA-KFUPM Joint Research Center for Artificial Intelligence
10/2022 – 06/2023

  • Conducted a comprehensive literature review on semi-supervised learning methods for sign language recognition
  • Developed a semi-supervised model for sign language recognition using pose-based inputs and Transformer architecture
  • Ran multiple experiments to evaluate the model performance on the WLASL dataset
  • Collaborated with research team to publish findings in international venues

Research Intern

Undergraduate Research Office at KFUPM
06/2022 – 08/2022

  • Evaluated DarKnight, a privacy-preserving deep neural network training framework
  • Conducted empirical analysis using TensorFlow-based models on various datasets
  • Presented research findings at the SURE (Summer Undergraduate Research Experience) Exhibit Day
  • Gained experience in privacy-preserving machine learning techniques

📚 Publications

SSLR: A Semi-Supervised Learning Method for Isolated Sign Language Recognition
Hasan Algafri et al.
2025 | arXiv:2504.16640

  • Designed a novel semi-supervised learning framework addressing the challenge of limited labeled data for sign language recognition
  • Utilized pose-based inputs and Transformer backbone architecture for improved performance
  • Demonstrated significant improvements over baseline methods on standard benchmarks

Style Change Detection using Discourse Markers
Hasan Algafri et al.
2022 | CEUR Workshop Proceedings

  • Developed a classification algorithm to detect style changes in multi-authored documents
  • Implemented discourse marker analysis for improved detection accuracy
  • Published and presented at CLEF PAN 2022 conference

Last updated: August 2025