RESEARCHING AI HARDWARE
RESEARCHING THE FUTURE,
RESEARCHING AI HARDWARE RESEARCHING THE FUTURE,
Exploring how embedded computing, artificial intelligence, and hardware-aware system design can address challenges in energy, autonomy, and scientific observation.
DAYTONA BEACH ENERGY RESEARCH
STATUS: COMPLETED
Intro…
AI HARDWARE GRID APPLICATIONS RESEARCH
STATUS: ONGOING
Intro…
Interests Moving Foward…
Quantum Computing
Quantum computing uses quantum-mechanical behavior to process certain problems differently from conventional computers. I am interested in researching quantum processor architecture, control electronics, error correction, and hybrid quantum-classical computing systems.
MACHINE LEARNING ACCELERATORS
Machine-learning accelerators are specialized processors designed to execute AI workloads with greater speed and energy efficiency. I’d like to research hardware architectures that reduce inference latency, memory usage, and power consumption on embedded and edge devices.
Radiation-Tolerant & Extreme Hardware
Radiation-tolerant hardware is designed to operate reliably in space, high-radiation environments, and other extreme conditions. I’d love to dive deeper in researching fault detection, redundancy, resilient processor design, and embedded systems capable of continuing operation after hardware errors.
LETS BUILD SOMETHING
I’m seeking internship opportunities where I can contribute to embedded systems, computer architecture, FPGA development, and AI hardware while continuing to grow as an engineer.
Whether you’re interested in my work, discussing an opportunity, or connecting over engineering, I’d be glad to hear from you!