Making ideas work in the real world.

I move between computer vision, robotics, embedded hardware, and web software because the most interesting problems rarely stay inside one discipline. A good project can require an algorithm, a circuit, and a lot of patient testing.

My process usually starts by building a working version, finding the constraint that matters, and iterating until the result is useful outside the lab. Competition robotics taught me how quickly theory meets reality; power electronics and vision projects keep pushing that lesson in different directions.

Right now, I’m exploring ways to make intelligent systems more reliable and more tangible—especially where sensing, computation, and hardware need to work together.