Hello, I'm Gary Kanyuh

I have a strong foundation in Fusion 360 and SolidWorks, and can confidently model parts, assemblies, and mechanisms. I understand constraints, tolerances, and basic manufacturable design principles. I rated myself at 50% because I want to improve my speed, deepen my knowledge of simulation-driven design, and master more advanced workflows such as surfacing, generative design, and FEA-integrated modeling.

I am comfortable using AI tools to speed up engineering research, automate repetitive tasks, and improve efficiency. I understand prompting, workflow design, and how to apply AI to real engineering problems. I chose 50% because I am still expanding into technical AI integration—APIs, automated pipelines, model tuning, and building AI-driven systems.

I have hands-on robotics experience through avionics and embedded systems work, including sensors, microcontrollers, and mechanical integration. I understand control basics and system behavior. I rated myself at 50% because I want to advance in control theory, sensor fusion, autonomous navigation, and full-system integration.

I have a solid understanding of circuits, microcontrollers, wiring, sensors, and basic PCB concepts. I can prototype and debug hardware systems effectively. I gave myself 55% because I want to improve in PCB layout, signal conditioning, high-speed design, and architecting more complex embedded systems.

I am skilled at learning new technical material, analyzing data, finding patterns, and applying research to real engineering problems. My academic and project experience have helped me think critically and synthesize information. I chose 60% because I am still developing deeper research abilities—literature mastery, modeling, and producing formal technical documentation.

I understand FEA fundamentals including meshing, constraints, loads, deformation, and stress/strain interpretation. I have completed structural and vibration analyses through coursework and projects. I rated myself at 50% because I want to grow into nonlinear analysis, dynamic response, mesh optimization, and using FEA to drive high-level design decisions.

I have a developing understanding of sustainable engineering principles, material choices, and lifecycle impact. I can evaluate sustainability considerations at a high level. I rated myself 45% because I want deeper experience with LCA tools, sustainable material selection, and applying quantitative environmental metrics to engineering design.

I understand programming fundamentals and can build automation tools, integrate APIs, and write problem-solving scripts. I am comfortable in Python and have experience with JavaScript through web development. I rated myself at 40% because I want to improve my algorithmic thinking, learn advanced data processing, and structure larger engineering software projects.