Chaehong Lee is a product-minded AI engineer based in NYC, with a background in computer vision, LLMs, and generative models. She specializes in transforming state-of-the-art research—like function-calling agents, Stable Diffusion pipelines, and edge-native vision systems—into polished, real-time products that feel intuitive and expressive to use.
Currently at Meta Reality Labs, and formerly at Microsoft Mixed Reality, she brings technical depth with strong systems thinking, shipping experience, and visual design instincts. Her recent work spans sparse autoencoder interpretability, multimodal prompt interfaces, and agentic tool-calling.
Open to AI-first teams and startups—especially in NYC, SF, or remote—building next-gen tools at the intersection of usability, creativity, and machine intelligence. Also open to software solutions architect consulting opportunities where strategic technical insight and user-centered design can bring research to life.
Lately, I've been thinking about how images are represented in feature space-
Where in a neural network does the vibe of an image actually reside?
In this study, I explore the potential of AI-assisted design in transforming natural forms and original artwork into complex, aesthetically pleasing patterns suitable for fashion applications. The process begins with either a hand-drawn sketch or a photograph of a natural object, which serves as the seed for stable diffusion models.
Methodology:
Learning:
+ the positives.
- the negatives.
This study demonstrates the potential of AI as a collaborative tool in the creative process, expanding the possibilities of pattern design while maintaining a connection to the artist's original vision or natural inspiration.
Street style:
