Machine Learning · Generative AI · LLMs · Embedded Intelligence
From optimizing AI models to deploying scalable solutions across cloud and edge platforms, I transform complex ideas into practical, real-world technologies.
Hi, I'm Arya Rajesh Chandrawanshi, a Computer Engineer with a Master's degree in Computer Engineering from George Mason University. My interests lie at the intersection of Artificial Intelligence, Machine Learning, Generative AI, Embedded Systems, and Intelligent Computing.
I enjoy building end-to-end AI solutions — from training and optimizing machine learning models to deploying real-world applications using LLMs, RAG pipelines, cloud platforms, and edge devices. My work spans Generative AI, GPU Programming, Neuromorphic Computing, IoT, and Embedded AI systems.
I'm passionate about solving real-world problems through technology and continuously exploring emerging advancements in AI and intelligent systems.
Click any card to see the full write-up — aim, methodology, results, and impact.
Researched orthogonal GPU memory-reduction techniques for LLM training, benchmarking 8 technique combinations and applying Bayesian Optimization to reach >61% VRAM reduction validated on real WikiText-2 data.
Built Python data-processing scripts and delivered instruction in algorithms and statistics, supporting 30+ students per semester with grading, assignment design, and academic feedback.
Mentored students in Python, Azure GenAI, RAG pipelines, LLM engineering, and GPU-accelerated ML across embedded systems, signal processing, and machine learning courses.
Coordinated academic accommodation services and documentation workflows, improving operational efficiency while maintaining confidentiality and compliance standards.
Applied Python and systematic testing in a government-certified standards lab — sensor interfacing, microcontroller data acquisition, and calibration workflows alongside senior engineers.
I'm actively looking for full-time roles in AI/ML engineering, embedded systems, or edge computing. F-1 OPT — available immediately.