PeopleofSuperintelligence

Researcher

Charles Ding

Charles Ding is an AI researcher whose work examines multimodal agents and parallel text generation. He was a first-year information-systems student at Carnegie Mellon in 2023 and worked as a software engineer at NVIDIA in 2024. In 2024, he coauthored VideoWebArena, a benchmark of 2,021 web-agent tasks that tests skill retention and retrieval of facts from long video tutorials. He began a master's program at Stanford in 2025 and coauthored a language-model creativity study that received the ICML Outstanding Paper Award. Since 2026, he works in Tesla's Optimus AI group; in October 2026, he coauthored Next-Concept Modeling, which generates increasingly detailed text representations in parallel.

Now at
Tesla
Badges

Timeline

  1. 2022–2025

    Undergraduate study at Carnegie Mellon

    He studies as an undergraduate at Carnegie Mellon from 2022 to 2025. In 2023, he is a first-year information-systems student and competes in the Quant Club's Market Making Game.

  2. 2024

    Software engineer at NVIDIA

    In 2024, he works as a software engineer at NVIDIA.

  3. 2024

    VideoWebArena benchmark

    In 2024, he coauthors VideoWebArena, a benchmark of 2,021 web-agent tasks that tests skill retention and retrieval of instruction-relevant facts from long video tutorials.

  4. 2025–2027

    Stanford master's student

    From 2025 to 2027, he is an MS student at Stanford.

  5. 2025

    Creative limits of language models

    In 2025, he coauthors Roll the dice & look before you leap, which uses minimal algorithmic tasks to measure language models' creative limits. It argues that next-token learning is myopic and memorizes excessively. The paper finds that teacherless training and diffusion models produce diverse, original output.

  6. 2025

    ICML Outstanding Paper Award

    He shares the 2025 ICML Outstanding Paper Award with Vaishnavh Nagarajan, Chen Henry Wu, and Aditi Raghunathan for Roll the dice & look before you leap.

  7. October 2026

    Next-Concept Modeling

    In October 2026, he coauthors Next-Concept Modeling, a language-model framework that generates text from coarse concepts to fine details and predicts all codes within each level in parallel.

  8. Since 2026

    Tesla's Optimus AI group

    Since 2026, he works in Tesla's Optimus AI group.

Career

  1. Since 2026Tesla
  2. 2024NVIDIASoftware Engineer

Education

  1. 2025Carnegie Mellon University
  2. Stanford UniversityMaster's degree

From the biography.

  1. 16% of AI career moves in the 2020s went from a university to a companyIncludes Charles Ding. We estimate that 16% of AI career moves in the 2020s went from a university to a company; 29% of moves starting at a university went to a company, and 76% ended the university role.
  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 Tesla. 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 Tesla. 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. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Tesla. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.

Colleagues

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

Sources and credits

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

  1. Market Making Game Participants Trade Winning Strategies cmu.edu. Checked 21 October 2026.
  2. Charles Ding (Tesla) — Lacuna lacuna.tiptreesystems.com. Checked 21 October 2026.
  3. VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks arxiv.org. Checked 21 October 2026.
  4. Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction arxiv.org. Checked 21 October 2026.
  5. Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction arxiv.org. Checked 21 October 2026.
  6. Aditi Raghunathan's Group @ ICML 2025 cs.cmu.edu. Checked 21 October 2026.
  7. ICML 2025 Awards icml.cc. Checked 21 October 2026.
  8. Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation hazyresearch.stanford.edu. Checked 21 October 2026.
  9. Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation arxiv.org. Checked 21 October 2026.