Welcome to my personal portfolio. I am a Computer Science Engineering student at VIT Vellore who enjoys building practical software across AI/ML, full-stack development, cybersecurity, automation, and edge systems.

• Interests: AI/ML, information retrieval, cybersecurity, developer tools, automation, and embedded systems
• Languages: Python, TypeScript, JavaScript, Kotlin, Java, C++, Dart, Bash, HTML, and CSS
• RoboVITics: Member of the AI/ML and Cybersecurity domains
• Current focus: Building reliable, evidence-driven applications that connect machine learning with useful real-world workflows

An AI-assisted application that turns an example video into a step checklist and compares later recordings to identify skipped, reordered, or uncertain actions. Uses SAM for visual grounding and rule-based checks for explainable results.

A native Android app built with Jetpack Compose, SQLite, ML Kit OCR, and WorkManager. It tracks return and warranty deadlines, extracts receipt details on-device, sends local reminders, and exports evidence and backups without requiring an account or backend.

A local tool for importing CSV telemetry, replaying timelines, inspecting channels and CAN frames, and comparing expected and predicted labels. Includes validation, statistics, SQLite persistence, and exportable experiment reports.

A traceable earth-observation notebook for comparing NASA satellite browse images across dates, recording observations, preserving source requests, and exporting investigation reports.

A web workbench for comparing lexical retrieval baselines against relevance judgments. It evaluates precision, recall, MRR, and nDCG while preserving datasets, parameters, rankings, and experiment results.

A community-operated platform for surplus-food redistribution. It supports donor listings, receiver claims, volunteer pickup and delivery, role approval, expiry processing, trust history, and scoped impact reports.

An AI/ML pipeline using NASA FIRMS data to predict next-day fire occurrence on a spatial grid. It compares multiple classifiers, uses time-series validation and feature ablation, and provides an interactive map and metrics dashboard.

A zero-dependency macOS and Linux utility for captive-portal auto-login, WiFi monitoring, speed tests, data-usage history, network scanning, notifications, and background daemon support.

An ESP32 edge-computing project for TinyML-based EV monitoring and guardian features.

An exploration of graph-powered retrieval and AI workflows.

• Member of RoboVITics in the AI/ML and Cybersecurity domains
• Contributor during Hacktoberfest
• Building and sharing projects that combine software engineering with machine learning and systems work

Each project repository includes its own setup instructions, technology details, validation notes, and development documentation. Browse the projects above to see the implementation and run them locally.

• Email: ryanfernandes23816@gmail.com
• LinkedIn: linkedin.com/in/ryanfernandes1
• GitHub: github.com/ryanfer123

Thanks for visiting my portfolio!