I'm Jeffrey, a technologist applying AI and deep learning to physical systems.

I'm experienced in startups, specializing in systems engineering, product strategy, and platform development for AI-enabled hardware-software systems. I’ve led innovation across industries including automotive, clean energy, and developer tooling.

I've completed my Master of Science in Artificial Intelligence at UT Austin. I’m passionate about leveraging AI to drive innovation.

An Intuitive Explanation of SGD vs Gradient Descent

An intuitive exploration of why Stochastic Gradient Descent often outperforms traditional gradient descent in machine learning optimization, from data efficiency, a focus on progress, and leveraging randomness.

Auditing Stable Diffusion with Perplexity

I used prompt engineering and RAG to have Perplexity's Default LLM design a process for a demographics fairness audit of the Stable Diffusion v2.1 text-to-image model.

Generative AI as an Ethical Theorist

I used prompt engineering and RAG to get LLMs to pose as ethical theorists and react to a contemporary AI ethics dilemma, the potential adoption of social robots within public facilities for vulnerable and special needs children.