Autonomous AI agent that analyzes, summarizes, and enhances developer portfolios using LLMs. Designed to evaluate projects, generate insights, and suggest improvements for stronger personal branding.
About
AI Engineer with experience in data science, machine learning, and Python development. I design and deploy models for heterogeneous data, including images, text, time series, and tabular datasets, and build reproducible pipelines using tools such as Docker, Git, FastAPI, and vector databases.
My work sits at the intersection of applied research and production systems: from radiomics and survival prediction in medical imaging to RAG assistants, semantic retrieval, and intelligent SaaS features.
LLMs & RAG
Multimodal ML
Medical Imaging
FastAPI
Docker
Vector Search
Building LLM pipelines, semantic search workflows, and scalable AI systems that move beyond notebooks into usable products.
Working on survival prediction, radiomic feature engineering, and clinically oriented multimodal modeling.
Strong emphasis on clean pipelines, benchmarking, deployment, and making AI systems robust enough for real environments.
Experience
Applied AI experience spanning startup products, medical research, and production pipelines.
Built LLM pipelines for note structuring, summarization, extraction, and prioritization. Implemented semantic search with embeddings and pgvector, designed ingestion-to-insight pipelines, and integrated AI modules into a React, Django REST, and Supabase architecture.
Developed a multimodal survival prediction model for lung cancer using MRI, PET, and clinical data on 180+ patients. Defined and validated new radiomic features integrated into LIFEx, with a scientific manuscript in preparation.
Rebuilt a radiomics extraction pipeline on brain MRI, optimized it through multi-CPU parallelization, reduced runtime by 40%, containerized the workflow with Docker, and developed predictive models for genomic mutations.
Featured Projects
Full-stack AI assistant integrating a Chrome extension (MV3) with a FastAPI backend using Gemini, providing contextual text rewriting, translation, and persistent knowledge capture directly in the browser, with structured note management and export capabilities.
LegalChatbot
↗Intelligent Lebanese legal assistant built for Arabic question answering using a RAG architecture combining SBERT, Gemini, FastAPI, and React.
MediNetFusion
↗Multimodal time-series classification project for early type 2 diabetes prediction using 77 biomarkers over 12 months with models including CNN, LSTM, and XGBoost.
SISSI AI Assistant
↗AI-powered executive assistant SaaS centered on note structuring, semantic retrieval, and insight generation through modern LLM workflows.
Hospital Flow Optimization
↗Optimization work on emergency department logistics using real-world hospital data, scheduling, prediction, multi-agent systems, and IoT-driven analysis.
LLM Picker Extension
↗Utility project focused on improving day-to-day AI workflow ergonomics through a practical extension-oriented interface.
Gym Membership Manager
↗Software project demonstrating practical backend and data handling skills through a management-focused application.
Skills
Core engineering stack across machine learning, MLOps, data systems, and software development.
AI / ML
PyTorch, TensorFlow
NLP, LLMs, prompt engineering
RAG, embeddings, semantic search
Supervised & unsupervised learning
Multimodal modeling
MLOps & Deployment
FastAPI, Streamlit, Gradio
Docker, Git, Linux shell
MLflow
Elasticsearch, pgvector
Reproducible pipelines
Data & Research
NumPy, Pandas, scikit-learn
Feature engineering & benchmarking
Spark, Power BI
Medical imaging & radiomics
Optimization algorithms
Programming
Python, Java, C
SystemVerilog, MATLAB, R, SQL
HTML, CSS
GitHub, GitLab, VS Code
SPARQL, UML / SysML
Education
Graduated with High Honors, with advanced work in artificial intelligence applied to healthcare systems.
High Honors. Built a strong foundation in electronics, microcontrollers, signal processing, robotics, and medical systems engineering.
Languages
Arabic — Native
English — C1
French — C1
Career Direction
Looking to contribute as an AI Engineer, Applied AI / LLM Engineer, or AI-focused Data Scientist in teams building useful, scalable systems.
Let’s build something serious.
Interested in AI engineering, LLM systems, multimodal learning, healthcare AI, or production-ready ML? Reach out through any of the channels below.
Quick Snapshot
LLM systems, semantic retrieval, multimodal prediction, radiomics, and deployable ML backends.
Focused on performance, structure, reproducibility, and practical impact rather than flashy demos.
Comfortable in startup contexts, research labs, and interdisciplinary teams solving hard real-world problems.