Chenkai Mao

About Me

I am a research engineer at OpenAI. I work on kernel optimization and pretrain scaling.

Previously, I was a postdoc researcher at Stanford University. My research interests are:

1. AI for science (PDE modeling and inverse design)
2. Nanophotonics design and fabrication
3. Additive manufacturing

I completed my PhD at Stanford, advised by Prof. Jonathan Fan. Before that, I received my Bachelor’s degree from MIT in EECS and Physics, advised by Prof. Marin Soljačić. I interned at FAIR Meta, Apple and Lawrence Livermore National Lab. You can check out my CV here.

News

• [May 2026] I joined OpenAI as part of the Workload team in the Research organization. I work on kernel optimization and pretrain scaling.
• [Apr. 2026] Our paper “Accurate and scalable deep Maxwell solvers” is published in PNAS!
• [Dec. 2025] Our paper “3D nanolithography with metalens arrays and spatially adaptive illumination” is published in Nature!
• [Nov. 2025] I defended my PhD dissertation titled “AI-Enabled Co-design for Compuational and Physical Nanophotonics Systems”.
• [Oct. 2025] I help organized the Machine Learning theme for Frontier in Optics conference in Denver. I moderated the panel discussion of “The Future of AI in the Design of Optics and Photonics”
• [June. 2024] Our paper “Towards General Neural Surrogate Solvers with Specialized Neural Accelerators” is accepted to ICML 2024.

Publications