Arjun Ramadas Menon

About

Computer Engineering student at Pillai College of Engineering with hands-on experience in web development, machine learning projects, and database-backed applications. Interested in software development, cybersecurity, cloud computing, and database engineering.

Education

• Bachelor of Technology
  Pillai College of Engineering · University of Mumbai
  Computer Engineering · 2023 – 2027
• Higher Secondary
  KM Agrawal College
  2023
• High School
  Shri Vani Vidhyashala High School
  2021

Skills

• C <3 months
• CSS <3 months
• Cloud Computing <3 months
• HTML <3 months
• Python <3 months
• Machine Learning <3 months
• JavaScript <3 months
• Node.js <3 months
• Cybersecurity <3 months
• Pandas <3 months
• scikit-learn <3 months
• React <3 months
• Flask <3 months
• PHP <3 months
• Random Forest <3 months
• Software Development <3 months
• Full-stack Development <3 months
• XGBoost <3 months
• Database Engineering <3 months
• Isolation Forest <3 months
• Q-Learning <3 months
• Scapy <3 months

Tools / apps / platforms

• Cursor <3 months
• Docker <3 months
• Git <3 months
• Kali Linux <3 months
• Linux <3 months
• Microsoft Windows <3 months
• MongoDB <3 months
• MySQL <3 months
• PostgreSQL <3 months
• Render <3 months
• VS Code <3 months

Languages

• English Speak
• Marathi Speak
• Hindi Speak
• Malayalam Speak

Projects

• NGO Web Application Platform
  HTML, CSS, JavaScript, PHP, MySQL, Render

  Designed and developed a responsive web platform to streamline donation processing, volunteer engagement, and campaign tracking. Integrated secure server-side validation, relational database storage, and custom contribution workflows to ensure reliable transactions.

• Food Waste Management System
  Python, XGBoost, Scikit-Learn, Pandas, HTML, CSS, Flask, JavaScript, Joblib, Chart.js

  Developed a system focused on reducing surplus food wastage by optimizing resource allocation and coordination between donors and receivers. Built user interaction modules, managed database flows, and enabled accurate tracking of excess food availability.

• Self-Healing ML-Driven Pre-Firewall Packet Sanitization System
  Python, Machine Learning, Scikit-learn, Scapy, XAI, Random Forest, Isolation Forest, Q-Learning, Firewall

  Developing an adaptive cybersecurity system that utilizes machine learning to intercept and sanitize malicious network packets prior to firewall processing. Applied anomaly detection and reinforcement learning concepts to build a self-healing threat defense model through team research and optimization.

Courses & certifications

• Deloitte Virtual Internship · Deloitte

⚽ Extracurricular activities

• Hackathon Participation
• Technical Events