Richard Zhang, 34, a senior research scientist at Adobe, invented the visual similarity algorithms underlying image-generating AI models like Stable Diffusion and Stylegan.

Zhang began exploring generative AI while completing his PhD at UC Berkeley, where he created a widely used algorithm to colorize black-and-white photos. (This work turned into the Colorize tool in Adobe Photoshop.)

In doing this work, Zhang realized there was no “good objective metric” to train the AI system. “It’s really hard to write a map [of] what makes an image look good to a person,” he says, whether that means realistic colors or image clarity.

Most algorithms use mathematical models to measure how similar different images look to human viewers, but human perception is complex and not easily captured by a math problem. So Zhang built something better: LPIPS, his most influential project to date.

LPIPS is unique in incorporating big data sets of human perceptual judgments into its computations. This has helped it outperform all previous models, many of which had been in use for decades, and become the new standard for perceptual similarity. Without LPIPS,today’s image-generation AI would not be possible.

Since he joined Adobe in 2018, Zhang’s research has been incorporated into commercial software tools, including Photoshop’s landscape mixer and smart portrait features. Zhang has also worked on algorithms that help people detect images generated by AI, which are now part of Adobe Stock’s forensic tools.