Software Engineer & Privacy Researcher
Specialising in OSINT tools, scalable data pipelines & open-source software.
Hi, I'm
I'm Rushikesh — I build privacy-first tools and open-source software at the intersection of data science, OSINT 🔍 and systems engineering.
Focused on building real, deployable software — from intelligent data pipelines and OSINT engines to scalable APIs and privacy-respecting digital tools. Every project ships clean, documented, and open.
Python, JavaScript, C, C++, SQL — building scalable, efficient systems from the ground up.
Building privacy-focused engines and digital footprint analysis tools for security researchers.
Data modeling, analysis and beautiful visualizations using Chart.js and modern pipelines.
From self-hosted infrastructure to AI-powered systems — a look at what I've been building.
A privacy-first home server built from the ground up on Ubuntu Server with LVM. CloudNest swaps everyday cloud services — storage, photo backup and DNS — for self-hosted, self-controlled alternatives, all managed through CasaOS.
Deep learning-powered MRI brain tumor detection system using transfer learning for accurate classification and early diagnosis assistance. Built with an end-to-end pipeline including model training, REST APIs and a responsive web interface.
An AI-powered virtual assistant that understands natural language, automates everyday tasks, answers questions, and delivers an interactive conversational experience using modern large language models.
A machine learning-powered phishing detection system that analyses suspicious emails, identifies malicious content, and helps protect users against evolving phishing attacks.
A complete admission management platform that streamlines student registration, document verification, merit list generation, and administrative workflows for educational institutions.
Currently researching and designing my capstone project focused on Artificial Intelligence, Cloud Computing and scalable software systems. The project will be announced soon.
Peer-reviewed research publications in Artificial Intelligence, Computer Vision, Deep Learning, Medical AI and Educational Technology.
Developed an end-to-end AI-powered brain tumor detection system using the VGG16 deep learning architecture. Built a complete pipeline consisting of model training, REST APIs with Flask & FastAPI, and a React.js web application capable of delivering accurate real-time MRI predictions.
Designed and developed a comprehensive admission management platform that digitizes student registration, eligibility verification, document management, merit list generation and administrative workflows, significantly improving efficiency, transparency and reducing manual processing time.
Currently working on innovative research in Artificial Intelligence, Machine Learning, Computer Vision, Large Language Models and intelligent software systems, with future publications planned in peer-reviewed journals.