Garegin Mazmanyan

About Me

I'm a computer science graduate student at the University of Arizona, specializing in the intersection of full-stack development and machine learning. My passion lies in building scalable, intelligent systems that solve real-world problems.

                            
                            MS in Computer Science
University of Arizona

                            
                            AI Robotics Research
University of Arizona

                            
                            AWS Certified
3 Professional Certifications

Professional Timeline

2025 - Present

Engineering Robotics Lab

University of Arizona

Leading autonomous driving research that integrates computer vision with natural language processing to develop intelligent vehicle systems. My current project focuses on creating multi-modal autonomous agents capable of interpreting spoken commands while providing real-time explanations of driving decisions. This research advances the field by bridging the gap between mechanical automation and truly intelligent robotic systems.

Python C/C++ Computer Vision Deep Learning TensorFlow PyTorch ROS2 AI Research

2024 - Expected 2026

Master of Science in Computer Science

University of Arizona

Pursuing an accelerated master's program that enables concurrent completion of graduate coursework while finishing undergraduate requirements. Specializing in artificial intelligence and machine learning with emphasis on practical applications in autonomous systems. The program provides advanced theoretical foundation combined with hands-on research experience in cutting-edge robotics and intelligent systems development.

Machine Learning Deep Learning Artificial Intelligence Computer Vision NLP Research Methods Advanced Algorithms Data Structures

2024 - 2025

Software Engineer Intern

AEYESAFE

Developing and implementing scalable cloud infrastructure solutions while gaining comprehensive industry experience in modern software development practices. Successfully migrated legacy applications to AWS cloud architecture, utilizing containerization technologies and automated CI/CD pipelines. Achieved 50% reduction in deployment time through strategic implementation of Docker-based workflows and collaborated effectively with cross-functional teams to deliver robust software solutions.

Docker AWS ECS Fargate DynamoDB Lambda API Gateway CI/CD Python YAML

2021 - 2025

Bachelor of Science in Computer Science

University of Arizona

Established comprehensive foundation in computer science fundamentals while developing leadership experience through teaching roles. Served as Undergraduate Teaching Assistant and Course Coordinator, mentoring over 300 students in software development and programming concepts. Earned multiple professional certifications including AWS Cloud Practitioner, AWS Developer Associate, and AWS Machine Learning Specialty. Successfully balanced academic excellence with practical skill development in cloud technologies and modern software engineering practices.

Python Java JavaScript React Node.js HTML/CSS SQL MongoDB Git AWS Certified Teaching

Featured Projects

CSC110 Coding Platform

A comprehensive educational platform revolutionizing computer science education. Features include an interactive code editor with syntax highlighting, real-time Python execution environment, automated test validation, and progress tracking. Increased student engagement by 40% and improved learning outcomes through immediate feedback mechanisms.

🔹 Real-time code execution 🔹 Automated testing 🔹 Progress analytics 🔹 Interactive learning

React.js Node.js Express.js PostgreSQL JWT Docker

Crazyswarm2 Affine Transformation

Advanced drone swarm coordination system implementing affine transformations for multi-robot formations using ROS2 and Crazyswarm2 framework. Developed geometric transformation algorithms for precise swarm choreography, enabling complex formation flying patterns and real-time coordinate system transformations for Crazyflie drones.

🔹 Swarm coordination 🔹 Affine transformations 🔹 Formation control 🔹 Real-time communication

ROS2 Python Crazyswarm2 NumPy Geometric Algorithms Crazyflie

QCar2 Autonomous Driving with Natural Language

Comprehensive autonomous driving system for QCar2 platform that combines vision-based navigation with natural language instruction following and real-time explanation generation. Developed multi-task deep learning model that simultaneously drives the vehicle, responds to text commands, and provides spoken explanations of driving decisions using camera input only.

🔹 Vision-based autonomous driving 🔹 Natural language instruction following 🔹 Real-time driving explanations 🔹 Multi-task learning architecture

ROS2 PyTorch Computer Vision NLP MobileNetV2 LSTM TensorRT Text-to-Speech

AI-Powered Portfolio

Professional portfolio website featuring timeline design and integrated AI chatbot assistant. Built with modern web technologies, includes smooth animations, responsive design, and intelligent conversation capabilities. Showcases career progression and technical expertise through interactive elements.

🔹 AI chatbot integration 🔹 Responsive design 🔹 Smooth animations 🔹 SEO optimized

HTML5 CSS3 JavaScript Particles.js AI API Progressive Web App