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Solves the "one-size-fits-all" education problem by adjusting question difficulty and learning paths based on real-time performance, mimicking a private tutor.

  • **Adaptive Practice**: Visual topic tree where nodes unlock as students prove mastery.
  • **Teacher Command Center**: Data-driven heatmaps and proactive struggle alerts.
  • **Custom BKT Engine**: Personalized learning journey through advanced probabilistic modeling ((L)$).
Python Django 5.1 BKT PostgreSQL LaTeX Bootstrap
MindTrack AI — Precision Learning for Every Mind preview
Feb/2026

FAWZY.AI

Lets visitors explore the portfolio conversationally and demonstrates end-to-end RAG, prompt constraints, deployment, and admin operations.

FAISS (k=6)

Retrieval

all-MiniLM-L6-v2

Embeddings

Groq (Llama)

LLM

On/Off + Refresh

Admin controls

  • RAG over knowledge files + Django DB content
  • Admin-controlled maintenance mode, tracking, and index refresh
  • Reduced redundant LLM calls for standalone questions
  • Optional FAISS persistence for faster restarts
  • Excel Q&A logging for evaluation/testing
Python FastAPI Django LangChain Groq Hugging Face FAISS OpenPyXL
FAWZY.AI preview

Led research and engineering for an AI system assisting hemodialysis teams with anemia management, pairing OCR pipelines with role-aware dashboards.

20+

Biomarkers

90%

Time Saved

99%

OCR Accuracy

  • Architected a robust Vision AI pipeline using Google Gemini to extract context-aware structured data from medical tables with 85-95% accuracy.
  • Engineered a high-resilience batch engine with a custom API Key Rotation & Failover system to handle high-volume processing and rate-limit bypass.
  • Integrated a longitudinal analytics dashboard that tracks 20+ biomarkers over time, helping clinicians identify health patterns 90% faster.
Python Django Next.js React TypeScript Google Gemini AI OCR REST API SQLite
LabLens AI – Intelligent Medical Data Extraction preview

An AI-powered clinical decision support system designed to automate anemia management for hemodialysis patients.

94%

OCR accuracy

1090

Patient visits digitized

0.6

Hb MAE

  • Directed a multi-member team, owning experimentation, model selection, and delivery.
  • Combined OCR and ML inference to extract lab metrics with reduced manual errors.
  • Built secure experiences for doctors, nurses, and patients plus a Flutter companion app.
Python TensorFlow Django Flutter OCR
AnemoCare — AI Anemia Management preview

Designed custom NLP pipelines for classification, similarity, and generation.

  • Designed custom NLP pipelines for classification, similarity, and generation.
  • Trained FastText models (custom + pretrained), improving Yelp dataset word similarity tasks.
  • Built LSTM & GRU-based models for text generation on Wikipedia data.
Python NLTK Spacy FastText LSTM GRU TensorFlow/PyTorch
Natural Language Processing Projects preview

Implemented Q-Learning & Value Iteration on OpenAI Gym’s FrozenLake-v1.

  • Implemented Q-Learning & Value Iteration on OpenAI Gym’s FrozenLake-v1.
  • Developed optimal policies for both stochastic and deterministic versions of the environment.
  • Compared performance of algorithms in stochastic vs deterministic environments.
Python OpenAI Gym Reinforcement Learning Q-Learning
Reinforcement Learning – FrozenLake AI Agent preview

Developed a VAE with reparameterization trick for robust latent space sampling.

  • Developed a VAE with reparameterization trick for robust latent space sampling.
  • Trained on CIFAR-10 RGB and a custom dialysis dataset linked to graduation project.
  • Created image interpolation functions for smooth transitions.
  • Extended model into a GUI tool for interactive image generation.
Python PyTorch VAE Computer Vision
Variational Autoencoder (VAE) preview

Evolved an autonomous Tetris agent that surpassed 10.3M points via GA-driven heuristics.

10.3M

Max score

250+

Generations

  • Implemented selection, crossover, and mutation strategies to iterate on candidate agents.
  • Instrumented training loops and telemetry to surface board-evaluation insights.
Python NumPy Genetic Algorithms
Tetris AI — Genetic Algorithm Optimization preview

Consolidated fragmented fitness workflows into a single web app, pairing real-time training analytics with scientific nutrition guardrails and coach-client collaboration.

1,746

Exercise library

15+

Muscle sub-groups

Per set

Real-time PR detection

Goal-based

Adaptive macros

  • Built an automated ingestion pipeline to maintain a 1,700+ exercise library with media and structured muscle mapping.
  • Implemented a set-level logging system with real-time Personal Record detection and dashboard visualization.
  • Delivered a scientific nutrition engine (Mifflin–St Jeor) with adaptive daily macro guardrails and guest-mode conversion.
  • Enabled coach-client workflows for assigning and updating training plans remotely.
Python 3.12 Django 5.0 SQLite PostgreSQL Django Unfold Chart.js Pillow
Gymee — Unified Fitness Intelligence Platform preview