About me
I like problems where good engineering and mathematics are needed.
I’m an applied mathematics student at UC Berkeley interested in the extension of mathematical understanding to the systems that shape up the real world.
I’m interested in how mathematical structure becomes software: how a model sees a floor plan, how an objective shapes what a learning system does, and how an interface helps a person make sense of complicated technical information.
Open résumé
What I’m studying
Applied mathematics gives me a way to move between theory and systems.
At UC Berkeley, I’m studying applied mathematics while building toward deeper work in machine learning, computer vision, reinforcement learning, probability, and optimization.
At Trisetra AI, that curiosity meets the physical world through floor plans, geometry, and spatial representations. At AMD, it met a different kind of complexity: technical error information and the interfaces people use to reason about it.
I’m still actively learning. That is part of what makes this work exciting.
Where I’m going
I’m trying to become capable of doing unusually difficult technical work well.
The work page has the concrete projects. The brain page has the questions I’m still carrying. The life page has the parts that make the rest of this make more sense.