Surya Raj Portfolio - AI & RF Systems Engineering ProjectsPORTFOLIO

Development of an autonomous space rover navigation system implemented on FPGA, featuring real-time obstacle detection and path optimization algorithms. The system utilizes hardware acceleration for efficient data processing and includes power-optimized control mechanisms.

Advanced agricultural monitoring system leveraging Edge AI and cloud computing for real-time crop analysis and yield prediction. Implements IoT sensors network for environmental monitoring, machine learning for predictive analytics, and cloud-based dashboard for comprehensive farm management.

Development of a System-on-Chip (SoC) based data acquisition system for real-time water quality monitoring. Features high-precision analog front-end, integrated signal processing, and low-power design implemented in TSMC 65nm technology.

Web-based music streaming platform built with Django, featuring personalized recommendations and advanced search capabilities. Implements responsive design and optimized audio streaming.

Advanced educational electronics kit featuring modular hardware components and companion mobile app for interactive learning. Designed to teach fundamental electronics, programming, and IoT concepts through hands-on experiments.

Design and implementation of a high-performance Low Dropout (LDO) voltage regulator with integrated smart power management features. Implemented in 65nm CMOS technology, featuring adaptive bias control and power-saving modes.

Modern single-page application built with Angular, featuring custom animations, responsive design, and optimized performance. Implemented with TypeScript and custom CSS architecture, following best practices for web development.

Command-line interface tool for automating Git and GitHub workflows. Features include repository management, automated commits, branch handling, and development environment setup using Python and Shell scripting.

Design and implementation of a two-stage operational amplifier optimized for Low-Dropout Regulator applications. Implemented in UMC 180nm CMOS technology with focus on power efficiency and stability.

Python-based virtual assistant utilizing Natural Language Processing for voice commands and task automation. Features include speech recognition, text-to-speech synthesis, and system control capabilities.