Alex Nichol
OpenAI researcher; first author of GLIDE, Improved DDPM, and Point-E; co-author of the HumanEval paper
Alex Nichol is a software developer and researcher who, per Nichol's homepage, works at OpenAI on deep learning research; Nichol's GitHub profile also lists OpenAI. Nichol is first author of "Improved Denoising Diffusion Probabilistic Models" and of GLIDE, and co-first author with Prafulla Dhariwal of "Diffusion Models Beat GANs on Image Synthesis", all released with MIT-licensed OpenAI codebases. Nichol is also first author of Point-E and co-author of Shap-E, two OpenAI systems for generating 3D content whose code and models are published under the MIT License. Nichol is among the authors of "Evaluating Large Language Models Trained on Code", the paper that describes the HumanEval problem set.1256781491011121334
Work
HumanEvalOpen-source code
Listed among the authors of "Evaluating Large Language Models Trained on Code" (2021); the MIT-licensed openai/human-eval repository is the evaluation harness for the HumanEval problem solving dataset described in that paper.34
Improved DDPM, guided diffusion, and GLIDE (external site: github.com)Open-source code
First author of "Improved Denoising Diffusion Probabilistic Models" (2021) and GLIDE (2021), and co-first author of "Diffusion Models Beat GANs on Image Synthesis" (2021). OpenAI publishes the official codebases (improved-diffusion, guided-diffusion, and glide-text2im, which runs the small filtered-data GLIDE model) under the MIT License.5678149
Point-E and Shap-E (external site: github.com)Open weights
First author of Point-E (2022) and co-author with Heewoo Jun of Shap-E (2023). Both OpenAI repositories are the official code and model releases for the papers and are licensed under the MIT License.10111213
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