Artificial Intelligence graduate with a GPA of 3.93/4.00 and hands-on experience in machine learning, computer vision, NLP, speech recognition, and data analysis. Skilled in object detection and segmentation using YOLO, …
Artificial Intelligence graduate with a GPA of 3.93/4.00 and hands-on experience in machine learning, computer vision, NLP, speech recognition, and data analysis. Skilled in object detection and segmentation using YOLO, fine-tuning Transformer models, LLM-based data augmentation, and speech recognition with Whisper and Wav2Vec2. Experienced in dataset development, annotation, model training, performance evaluation, and optimization.
<p>LinkedIn<br>
Jordanian Dialect Speech Recognition: Arabic speech recognition with Wav2Vec2 and Whisper, including dataset preparation, annotation, training and evaluation.<br>
Biofouling Detection Using YOLO: Developed a 2,531-image underwater dataset in collaboration with ship-maintenance companies in Aqaba, covering four biofouling severity classes.<br>
Trained and compared YOLO models, achieving a best test [email protected] of 0.707 with YOLOv8-S.<br>
Research presented at IAC 2025 in Sydney.<br>
Biofouling Segmentation: Extended biofouling analysis to instance segmentation by manually annotating underwater images with polygon masks using MakeSense.ai.<br>
Prepared YOLO-format segmentation data and trained YOLOv8 and YOLO11 segmentation models to localize fouling and support fouled-area estimation and 3D vessel digital twin integration.<br>
Arabic Sentiment Analysis: Developed a manually annotated Arabic tweet dataset with a team of five annotators to study vaccine hesitancy.<br>
Compared LSTM with attention, CNN-LSTM, AraBERT v1/v2, XLM-RoBERTa, and ELECTRA, with AraBERTv2 achieving the best results (77.29% accuracy and 75.74% F1-score).<br>
Research published at GACLM 2026.<br>
Additional Projects: Optimization Algorithms | Big Data | Game Development | Driver Distraction Detection | Flappy Bird (Pygame)</p>
<p>Prepared and processed noisy Arabic speech datasets for ASR systems, including audio preprocessing, text normalization, speech annotation, and quality validation.<br>
Contributed to developing speech recognition systems through high-quality dataset preparation.</p>
<p>Selected for the national startup incubation program based on an AI startup proposal.<br>
Worked closely with business mentors and technical experts.<br>
Participated in innovation and entrepreneurship workshops.</p>
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
د.جوب منطقة حرة ذ.م.م. 2026 © جميع الحقوق محفوظة
