I'm a security-focused developer and QA engineer with hands-on experience across software testing, cybersecurity, and machine learning. I've worked at Deloitte and as a Cyber Security Analyst, and I'm now actively building real-world projects at the intersection of ML and network security.
- 🔭 Currently building a Machine Learning Intrusion Detection System (IDS) from scratch
- 🌱 Learning React, AWS Cloud Services, and FastAPI
- 💼 Working as Quality Supervisor — web testing, load monitoring, quality assurance
- 🎓 Pursuing Master of Computer Applications (MCA) at Regent Education and Research Foundation
- 🛡️ Background in Pen Testing, Threat Analysis, and Endpoint Security
- ⚡ Fun fact: I'm building an IDS that can detect network attacks using Python and scikit-learn
Building a complete end-to-end IDS from scratch using Python and ML
- Training on the NSL-KDD dataset (125,000+ network connections)
- Implementing Logistic Regression → Decision Tree → Random Forest
- Achieved 95.3% accuracy with baseline model
- Backend API with Flask/FastAPI
- Frontend dashboard with React + Chart.js
- Tech Stack: Python, scikit-learn, pandas, Flask, React
🏢 Quality Supervisor | Black Burn Co | Jul 2025 – Present
🔐 Cyber Security Analyst | Cube Ai Solutions | Jun 2024 – Sep 2024
📊 Associate Analyst (QA) | Deloitte | Oct 2023 – Jan 2024
🎓 Master of Computer Applications (MCA) | Regent Education | 2025 – Present
🎓 Bachelor of Computer Applications | Narula Institute | 2020 – 2023 | CGPA: 8.88
⚛️ React & Full Stack Development
- HTML, CSS & JavaScript Fundamentals
- React — Components, Props, State, Hooks
- Built and deployed Task Manager App on Vercel
- Docker — Containerize Task Manager App
- Node.js + Express — Build backend API
- MongoDB — Connect to real database
- Authentication — Login / Signup system
- AWS — Deploy full stack app on cloud
🛡️ Machine Learning & Security
- Python Fundamentals
- Networking & Security Basics
- Machine Learning Fundamentals
- Data Preprocessing (NSL-KDD Dataset)
- Logistic Regression IDS Model (95.3% accuracy)
- Decision Tree & Random Forest Models
- Flask/FastAPI Backend
- React Frontend Dashboard
- AWS Cloud Deployment
- Real-time Packet Monitoring