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AlirezaRahi/README.md

👋 Hi, I’m Alireza Rahi

AI Security & Medical Imaging Researcher | Deep Learning Architect | Cryptographic Systems Engineer

About Me

I am a multidisciplinary researcher and engineer at the intersection of Trustworthy AI, Cybersecurity, and Precision Medicine. My work spans three critical domains: developing interpretable deep learning models for medical imaging and genomics, engineering AI-powered solutions for network intrusion detection, and implementing secure, production-grade systems using applied cryptography in Rust.
My journey began with a foundation in Computer Engineering and has evolved through independent research that bridges the gap between cutting-edge AI and real-world, safety-critical applications. I've contributed everything from benchmark medical datasets (the first globally balanced ALL/AML gene expression resources) and technical books on Vision Transformers to offensive security tools and secure authentication frameworks.
My overarching philosophy is simple: intelligent systems must be both powerful and trustworthy. Whether I'm segmenting brain tumors with Vision Transformers or building a secure Actix-web backend in Rust, my goal is to create solutions that are innovative, robust, and ready for deployment in high-stakes environments.

Research Interests

Medical AI: Deep Learning for Medical Imaging (MRI, fMRI, PET, CT), Genomic AI & Precision Oncology, Explainable AI (XAI) for Clinical Decision Support, Multimodal Data Fusion.
AI for Cybersecurity: Deep Learning for Intrusion Detection Systems (IDS), Anomaly Detection in Network Traffic, Malware Classification.
Secure Systems & Cryptography: Applied Cryptography in Rust, Secure System Architecture, Authentication/Authorization Protocols, Memory-safe Systems Programming.

Highlighted Projects

Medical Imaging & Genomics

Genomic Classification of ALL Using AI: Towards personalized medicine for leukemia.
AML Subtype Classification: Stacked deep learning for Acute Myeloid Leukemia subtyping.
Brain Metastasis Detection: Feature-based ML on clinical MRI data.
Skin Cancer Classification: Hybrid deep learning ensemble for dermatological analysis.
Cardiac Diagnosis from ECG: Deep learning for electrocardiogram analysis.

Cybersecurity & AI

Network Intrusion Detection: CNN-BiLSTM architecture for real-time multi-class attack detection. [Private/In-Progress]
Malware Classification: CNN-based architectures for binary analysis.
Secure User Management (Rust): Implementation of a secure authentication system using Argon2, Ed25519, and best cryptographic practices. [GitHub]

Security Engineering & Tooling

Web Vulnerability Scanner: A multi-threaded tool for detecting common web vulnerabilities (OWASP Top 10).
Multi-threaded Port Scanner with OS Detection: High-performance network mapping tool.
Network Security Tools Suite: A collection of utilities for network assessment.

Skills & Tools

Domain Skills & Tools

AI & Machine Learning Frameworks: TensorFlow, Keras, Scikit-learn. Architectures: CNNs, U-Net, Vision Transformers (2D/3D), Hybrid Models, Autoencoders. XAI: Grad-CAM, Feature Attribution.

Cybersecurity Network Security: Intrusion Detection (ML/DL), Penetration Testing Concepts (OSCP-oriented, CEH), Burp Suite, OWASP. Malware Analysis: CNN-based Classification.

Cryptography (Rust) Algorithms: AES, RSA, ECC, SHA-2/3, Ed25519, Argon2, bcrypt. Concepts: Symmetric/Asymmetric Encryption, Digital Signatures, Secure Key Management, TLS Fundamentals.

Backend & Systems (Rust) Frameworks: Actix Web.Concepts: RESTful API Design, Async Programming (Tokio), Secure Architecture, Memory Safety.

Medical Data & Imaging Formats: DICOM, NIfTI.Modalities: MRI, fMRI, PET, CT, X-ray, ECG. Libraries: Scikit-image, OpenCV.

Data Science & Tools Libraries: Pandas, NumPy, Matplotlib, Seaborn. Tools: Git, Linux (Advanced), Bash, VS Code.

Publications & Books

I am committed to open science, with all code and preprints publicly available.
Peer-Reviewed Preprints: 10+ preprints on medical AI (cardiac MRI, brain tumors, leukemia genomics, ECG analysis) available on medRxiv and TechRxiv.
Technical Books (First of Their Kind):
Mastering Grad-CAM with TensorFlow: From Theory to Medical Applications (Zenodo, 2025)
3D ViT in Medical Imaging: From Theory to TensorFlow Practice (Zenodo, 2025) – World's first guide on 3D Vision Transformers for medical imaging.
Vision Transformers in Medical Imaging: Foundations and Applications (Zenodo, 2025) – World's first dedicated guide on ViTs for medicine.
Comprehensive Guide to U-Net for Medical Imaging (Zenodo, 2025)

Datasets:

Global Balanced Gene Expression Dataset for ALL Subtypes (Zenodo, 2025)
Global Balanced Gene Expression Dataset for AML Subtypes (Zenodo, 2025)
Full list on: Google Scholar

Connect with Me

- GitHub
- Google Scholar
- LinkedIn

Fun Facts & Interests

First-of-their-Kind Contributions: Authored the world's first technical monographs on Vision Transformers, 3D Vision Transformers, and Grad-CAM specifically for medical imaging applications.

Benchmark Datasets: Created and published the first globally balanced gene expression datasets encompassing all subtypes of Acute Lymphoblastic Leukemia (ALL) and Acute Myeloid Leukemia (AML) .

Innovative Model Design: Developed a novel compact deep learning model ("mini-cardiologist") for end-to-end automated ECG analysis and diagnosis.

Security Tooling: Built and open-sourced a suite of practical network security assessment tools.

🧩 Beyond the Code

Neuroscience Enthusiast: Deeply fascinated by the brain—both as an organ to heal with AI and as an inspiration for new algorithms.

Science Communicator: I write detailed technical books and tutorials to mentor the next generation of AI researchers.

Nature & Chess: When I'm not coding or researching, you can find me hiking in nature or playing a thoughtful game of chess.

Open to Collaboration

I believe that the most impactful work happens at the intersection of disciplines. I'm always open to collaborating on projects related to:
Trustworthy AI in Medicine
AI-driven Cybersecurity
Secure Systems Engineering in Rust
Open-source Scientific Software

"Let's build intelligent, secure, and transparent systems that make a difference."

Popular repositories Loading

  1. A-Hybrid-Deep-Learning-Ensemble-for-Accurate-Skin-Cancer-Classification A-Hybrid-Deep-Learning-Ensemble-for-Accurate-Skin-Cancer-Classification Public

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  2. CAMUS-HeartNet-A-Deep-Meta-Ensemble-Architecture-for-Accurate-Cardiac-Tissue-Segmentation CAMUS-HeartNet-A-Deep-Meta-Ensemble-Architecture-for-Accurate-Cardiac-Tissue-Segmentation Public

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  3. network-security-tools network-security-tools Public

    Python tools for network security tasks

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  4. port-scanner port-scanner Public

    A multi-threaded port scanner with basic OS detection using TTL and TCP window size. Includes banner grabbing for open ports.

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  5. Python-Decorator-and-Context-Manager-Example Python-Decorator-and-Context-Manager-Example Public

    A simple Python example demonstrating the use of decorators and context managers for clean and reusable code.

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  6. Web-Vulnerability-Scanner Web-Vulnerability-Scanner Public

    A Python tool to scan for common web vulnerabilities including SQL Injection, XSS, and missing security headers.

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