AI/ML Security Research

PixRei

Building intelligent systems at the intersection of Machine Learning and Cybersecurity

About

Computer Science Student | AI/ML Researcher | Security Practitioner | E-Commerce Entrepreneur

Building intelligent systems at the intersection of Machine Learning and Cybersecurity. I'm a Computer Science student with hands-on expertise in both domains, focusing on practical solutions that detect, prevent, and respond to security threats using advanced ML techniques.

My approach combines rigorous penetration testing experience (25+ CTF boxes, 3+ security certifications) with deep learning research. I'm currently following an intensive 9-month ML mastery roadmap, progressing from fundamentals through production deployment, with a specialized focus on security applications.

While currently working on E-Commerce, I believe the future of cybersecurity lies in adaptive, intelligent systems—not static rules. Every line of code and every model I build is designed to make real-world impact.

25+
CTF Boxes Completed
2
ML Products Developing
2
Active Projects
3
Security Courses

Featured Projects

ML + Security in Action

📍 In Progress
🔍

Network Intrusion Detection

Building a Flask-based ML system for real-time network anomaly detection. Developing ensemble models using Scikit-learn to identify suspicious patterns in network traffic. Focus: accuracy, latency optimization, and practical deployment architecture.

Flask Scikit-learn Network Analysis Python
📍 In Progress
📧

Phishing Detection System

Developing an intelligent phishing detection system combining NLP and ML. Designing models to identify malicious URLs, phishing emails, and credential harvesting attempts. Targeting lightweight architecture for browser extension or API deployment.

NLP TensorFlow JavaScript Security
📋 Planning
🎯

Advanced Security ML Research

Planned research into adversarial robustness and concept drift in security ML models. Investigating production deployment challenges, model interpretability, and adaptive learning systems for real-world threat detection scenarios.

Research TensorFlow/PyTorch Adversarial ML Production ML

Development Workspace

pixrei@ml-researcher:~/projects
$ python train_model.py --phase ml-fundamentals
Initializing ML Fundamentals Phase...
Loading NumPy, Pandas frameworks...
Current Week 1-2 Focus: Array operations, DataFrames
Training Progress
Next Phase: Scikit-learn & First Projects
$

Skills & Expertise

Tools and technologies I work with

Machine Learning

  • NumPy & Pandas
  • Scikit-learn
  • TensorFlow / PyTorch
  • Model Deployment
  • Feature Engineering

Cybersecurity

  • Penetration Testing
  • Network Analysis
  • Security Research
  • Threat Detection
  • System Hardening

Programming

  • Python
  • JavaScript / HTML / CSS
  • Flask / FastAPI
  • Linux (I use Arch BTW)
  • Docker & Deployment
In Progress

9-Month ML Mastery Roadmap

Intensive learning path combining ML fundamentals with security specialization. Structured progression from theory to production-ready systems.

Phase 1 (Month 1/9) - Current: NumPy & Pandas (Week 1-2)

Phase 1
ML Fundamentals
Phase 2-3
Deep Learning
Phase 4-5
Security ML
Phase 6-7
Deployment
Phase 8-9
Polish & Launch

Learning Focus Areas

  • ✓ ML Foundations: NumPy, Pandas, Scikit-learn, Feature Engineering
  • ✓ Deep Learning: TensorFlow, PyTorch, CNN, RNN, Transformers
  • ✓ Security Applications: Malware detection, Intrusion detection, Adversarial ML
  • ✓ Production Systems: Flask, Docker, Model deployment, API design