PeopleofSuperintelligence

Researcher

Bogdan Damoc

Bogdan Damoc is a Google DeepMind researcher whose AI work spans retrieval-augmented language models, scaling laws and multimodal systems. He coauthored the RETRO paper in 2021, a routed language model scaling study in February 2022, and the Chinchilla compute-optimal training study in March 2022, which shared a NeurIPS 2022 Outstanding Paper award. His multimodal research includes the Gemini report in December 2023, the Gemini 1.5 long-context report in March 2024, and the Gemini 2.5 report in July 2025. Google DeepMind thanked him for developing and refining key Genie 3 components in August 2025, and since 2025 he is among the partners thanked for work on Veo 3 and Veo 3.1 components.

Timeline

  1. 2021

    RETRO and retrieved text

    In 2021, he coauthors “Improving language models by retrieving from trillions of tokens,” which introduces the Retrieval-Enhanced Transformer, or RETRO. The system enhances autoregressive language models by conditioning on document chunks selected from a large corpus for similarity to preceding tokens.

  2. February 2022

    Scaling laws for routing networks

    In February 2022, Damoc coauthors “Unified Scaling Laws for Routed Language Models.” The paper examines the scaling behaviors of routing networks, which conditionally use a subset of their parameters when processing an input.

  3. 2022

    Chinchilla and a NeurIPS award

    In March 2022, he coauthors “Training Compute-Optimal Large Language Models,” which finds that compute-optimal training scales model size and training tokens equally and tests the rule with the 70-billion-parameter Chinchilla model on Gopher's compute budget and four times more data. In November 2022, he shares a NeurIPS 2022 Outstanding Paper award with his coauthors for the compute-optimal training study.

  4. December 2023

    Gemini multimodal models

    In December 2023, he coauthors the Gemini report, which introduces a family of multimodal models for image, audio, video and text understanding.

  5. March 2024

    Gemini 1.5 at Google DeepMind

    With a Google DeepMind affiliation, he coauthors the March 2024 Gemini 1.5 report. The paper presents multimodal models that recall and reason across millions of tokens of context, including long documents and hours of video and audio.

  6. July 2025

    Gemini 2.5 report

    In July 2025, he coauthors the Gemini 2.5 report on models for advanced reasoning, multimodality, long context and agentic capabilities.

  7. August 2025

    Genie 3 world model

    Google DeepMind thanks him among the people who partner to develop and refine key Genie 3 components when it announces the interactive world model as a limited research preview in August 2025.

  8. Since 2025

    Veo 3 collaboration

    Since 2025, he is among the partners Google DeepMind thanks for helping develop and refine key Veo 3 and Veo 3.1 components.

  1. Google had the most people shaping AI every year from 2014 to 2025Includes Google. Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  2. Google has the highest combined h-index among AI organizationsIncludes Google. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  3. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Google. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.
  4. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes Google. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Bogdan Damoc yet. Send us a free-licensed photo.

  1. Improving language models by retrieving from trillions of tokens arxiv.org. Checked 21 October 2026.
  2. Unified Scaling Laws for Routed Language Models arxiv.org. Checked 21 October 2026.
  3. Training Compute-Optimal Large Language Models arxiv.org. Checked 21 October 2026.
  4. Announcing the NeurIPS 2022 Awards blog.neurips.cc. Checked 21 October 2026.
  5. Gemini: A Family of Highly Capable Multimodal Models arxiv.org. Checked 21 October 2026.
  6. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context arxiv.org. Checked 21 October 2026.
  7. Bogdan Damoc — themanybuilders.com themanybuilders.com. Checked 21 October 2026.
  8. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arxiv.org. Checked 21 October 2026.
  9. Genie 3: A new frontier for world models deepmind.google. Checked 21 October 2026.
  10. Veo 3.1 — Google DeepMind deepmind.google. Checked 21 October 2026.