PeopleofSuperintelligence

Researcher

Raphael Gontijo Lopes

Also known as Rapha Gontijo Lopes, Raphael Gontijo-Lopes

Raphael Gontijo Lopes is a machine-learning researcher whose papers span image robustness, data augmentation, ensembling and text-to-image generation. He was first author of the 2019 Patch Gaussian paper and the 2020 Affinity and Diversity paper, then co-authored the 2021 WiSE-FT and "No One Representation to Rule Them All" studies. In 2022, he co-authored Imagen, a text-to-image diffusion model whose paper won a NeurIPS Outstanding Paper award, and joined OpenAI, after four years of research at Google Brain, to build and launch ChatGPT. He is a research scientist at OpenAI, working on synthetic data.

Now at
OpenAI

Timeline

  1. 2019

    Patch Gaussian augmentation

    In June 2019, he is first author of the paper introducing Patch Gaussian, an augmentation that adds noise to randomly selected image patches and reaches state-of-the-art results on the CIFAR-10 and ImageNet Common Corruptions benchmarks. He also co-authors "A Fourier Perspective on Model Robustness in Computer Vision" with Dong Yin, Jonathon Shlens, Ekin D. Cubuk and Justin Gilmer, which finds that AutoAugment reaches state-of-the-art robustness on CIFAR-10-C.

  2. 2020

    Affinity and Diversity measures

    In February 2020, he is first author, with Sylvia J. Smullin, Ekin D. Cubuk and Ethan Dyer, of "Affinity and Diversity: Quantifying Mechanisms of Data Augmentation". The paper introduces two interpretable, easy-to-compute measures and finds that augmentation performance is predicted by jointly optimizing the two.

  3. 2021

    Ensembling across training methods

    In September 2021, he is one of eleven authors of "Robust fine-tuning of zero-shot models", which introduces WiSE-FT, a method that ensembles the weights of the zero-shot and fine-tuned models. In October 2021, he is first author, with Yann Dauphin and Ekin D. Cubuk, of "No One Representation to Rule Them All", a large-scale study in which two models of about 76.5% ImageNet accuracy form an ensemble that reaches 83.4%.

  4. May 2022

    Co-authoring Imagen

    In May 2022, he is one of the authors of "Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding", which presents Imagen, a text-to-image diffusion model. The paper reports that generic language models such as T5, pretrained on text-only corpora, are effective at encoding text for image synthesis.

  5. 2022

    A NeurIPS Outstanding Paper award

    In 2022, NeurIPS names the Imagen paper, which he co-authored, one of its Outstanding Papers.

  6. 2022

    Joining OpenAI for ChatGPT

    In 2022, after four years of machine-learning research at Google Brain, he and friends join OpenAI to build and launch ChatGPT.

  7. As of October 2026

    Synthetic data at OpenAI

    He is a research scientist at OpenAI, where he works on synthetic data after the 2022 move to build and launch ChatGPT.

Career

  1. Since 2022OpenAIResearch Scientist
  2. Until 2022Google Brain

From the biography.

  1. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Raphael Gontijo Lopes. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  2. Among employers with 30+ full-time cases, OpenAI leads primary technical role H-1B pay at $310,000, and Amazon, Google and Microsoft file 57% of all casesIncludes OpenAI. Across 440,669 certified US H-1B filings from 44 employers (FY2020–FY2026), OpenAI leads primary technical role base pay at $310,000 and xAI leads overall base pay at $290,000.
  3. 22 of 133 people shaping AI with a former OpenAI role now work at AnthropicIncludes OpenAI. Our estimates of where OpenAI recruits came from and where 133 people with former OpenAI roles work now, including the companies and labs they founded.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes OpenAI. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. [1906.02611] Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation arxiv.org. Checked 22 October 2026.
  2. [1906.08988] A Fourier Perspective on Model Robustness in Computer Vision arxiv.org. Checked 22 October 2026.
  3. [2002.08973] Affinity and Diversity: Quantifying Mechanisms of Data Augmentation arxiv.org. Checked 22 October 2026.
  4. [2109.01903] Robust fine-tuning of zero-shot models arxiv.org. Checked 22 October 2026.
  5. [2110.12899] No One Representation to Rule Them All: Overlapping Features of Training Methods arxiv.org. Checked 22 October 2026.
  6. [2205.11487] Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding arxiv.org. Checked 22 October 2026.
  7. NeurIPS 2022 Awards neurips.cc. Checked 22 October 2026.
  8. Announcing the NeurIPS 2022 Awards – NeurIPS Blog blog.neurips.cc. Checked 22 October 2026.
  9. Rapha Gontijo Lopes | Research Scientist at OpenAI rapha.computer. Checked 22 October 2026.