AI-focused Full-Stack Developer with a strong background in Computer Vision, Large Language Models (LLMs), AI evaluation, and intelligent mobile applications.

Experienced in developing and deploying AI-powered systems, optimizing model performance, building scalable applications, and integrating machine learning into real-world products.

• 🎓 Bachelor of Computer Science — Imam Mohammad Ibn Saud Islamic University (IMAMU)
• 🍎 Apple Developer Academy Graduate
• 💼 COOP at STC AI CoE Saudi Arabia
• 📍 Riyadh, Saudi Arabia
• 🌐 Portfolio: https://alanoudportfolio.framer.website
• 

• Computer Vision
• Large Language Models (LLMs)
• AI Evaluation & QA
• Natural Language Processing (NLP)
• Deep Learning
• iOS Development
• AI-Powered Applications
• Full-Stack Development

Python

Swift

JavaScript

C++

MATLAB

TensorFlow	PyTorch	Keras	Hugging Face	LangChain	Core ML	YOLO
OpenCV	NLTK

NumPy

Pandas

Jupyter

W&B

React

Node.js

Express

Flutter

Firebase

MySQL

MongoDB

Git	Docker	Xcode	VS Code	NetBeans	Postman
Figma	Sketch

🕵🏻‍♀️ Always exploring new tools and frameworks

• Designed and developed a YOLOv26-based object detection model (SPAF) for small-object UAV detection
• Proposed and integrated:
  • Sparse Vision Attention (SVA)
  • Progressive Bidirectional Auxiliary Pyramid Network (PBAP-Net)
  • Adaptive Channel Multi-scale Fusion Head (ACMF)
• Achieved:
  • +7.5% improvement in mAP@0.5 (46.8%)
  • Improved small-object detection on VisDrone2019
• Built and trained the model using:
  • PyTorch
  • Ultralytics Framework
• Conducted:
  • Full pipeline design
  • Ablation studies
  • Performance evaluation

• Developed and optimized Large Language Models (LLMs) for Saudi dialect NLP tasks
• Worked on:
  • Text classification
  • Text generation
• Applied:
  • LoRA
  • QLoRA
  • Quantization
• Evaluated models using:
  • Accuracy
  • BLEU score
  • Inference time
• Analyzed trade-offs between efficiency and accuracy

• Designed and implemented a compiler front-end for a custom programming language
• Built:
  • Lexical analyzer using DFA
  • Syntax analysis
  • Semantic analysis
• Implemented:
  • Symbol table management
  • Type checking
  • Error detection and recovery

• Developed a Core ML-powered budgeting system
• Generated personalized budgeting strategies based on user financial data

• Designed a gamified sign language learning platform
• Used animations and quizzes for accessibility-focused learning

• Built a location-based marketplace application
• Connected users with local businesses and deals

• Developed an accessibility-focused learning platform
• Designed for individuals with cognitive disabilities
• Used adaptive learning techniques

• Apple Developer Academy Program — Apple Developer Academy — Tuwaiq (2025)
• STEP — Standardized Test of English Proficiency — Score: 97
• Web Development Certifications:
  • HTML5
  • CSS
  • JavaScript
  • DOM
  • Bootstrap
• Backend Development Certifications:
  • Node.js
  • Express.js
  • MongoDB
  • MVC Architecture

• 📧 Email: alanoudssabaalkhail@gmail.com
• 💼 LinkedIn: https://www.linkedin.com/in/alanoud-abaalkhail
• 🌐 Portfolio: https://alanoudportfolio.framer.website
• 💻 GitHub: https://github.com/AlanoudSultan