PeopleofSuperintelligence

Researcher

D. Sculley

Sculley is a machine-learning researcher whose work spans scalable clustering, reliable ML systems, and generative-AI evaluation. He began working in machine learning around 2003 after teaching and studying art as an undergraduate, then earned a computer-science PhD at Tufts in 2008. His 2014 paper examined technical debt in machine-learning systems, and in 2019 he advised Google Brain researchers developing a deep-learning model for molecular odors. In 2024 he was Kaggle's CEO and joined the AI Mathematical Olympiad Prize advisory committee. Since 2025, he has been an OpenAI researcher focused on responsible and reliable machine learning and has coauthored a position paper on evaluating generative AI.

Now at
OpenAI
Works
54
Citations
8,312
h-index
30
Badges

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. By 2003

    From teaching to machine learning

    After several years as a teacher, he starts working in machine learning around 2003; as an undergraduate, he studies art.

  2. 2006–2008

    Teaching machine learning at Tufts

    At Tufts, he serves as a teaching assistant for Carla Brodley's Comp 250: Machine Learning course in 2006 and earns a computer-science PhD in 2008.

  3. 2010

    Web-scale k-means clustering

    He publishes Web-scale k-means clustering, which uses mini-batch optimization and projected gradient descent to address web applications' latency, scalability, and sparsity needs in 2010.

  4. 2014

    Technical debt in ML systems

    His 2014 NIPS workshop paper frames machine-learning maintenance costs as technical debt and identifies risks including hidden feedback loops and data dependencies.

  5. 2019

    Google Brain's odor model

    In 2019, he advises a Google Brain team whose deep-learning research predicts odor descriptors for molecules.

  6. 2024

    Kaggle CEO and AIMO advisor

    In 2024, he is Kaggle's CEO and joins the Artificial Intelligence Mathematical Olympiad Prize's advisory committee.

  7. Since 2025

    Responsible ML research at OpenAI

    In 2025, he is an OpenAI researcher focused on responsible and reliable ML and coauthors an ICML position paper arguing that AI competitions can provide rigorous evaluation for generative AI.

Career

  1. Since 2025OpenAIResearcher
  2. 2009–2022Google
  3. 2006Tufts UniversityTeaching assistant
  4. KaggleCEO

Education

  1. 2008Tufts UniversityPhD

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Web-scale k-means clustering2010 · International World Wide Web Conference (WWW) · 1,195 citations
  2. Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift2019 · 989 citationsWith Sebastian Nowozin
  3. Hidden technical debt in Machine learning systems2015 · neural information processing systems · 912 citations
  4. Ad click prediction2013 · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 868 citations
  5. Google Vizier2017 · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 572 citations

From OpenAlex, as of 19 October 2026.

  1. 13 of 79 people shaping AI with a former OpenAI role now work at AnthropicIncludes D. Sculley. Our estimates of where OpenAI recruits came from and where people with former OpenAI roles work now.
  2. The median h-index is 53 at universities and 19 at frontier AI labsIncludes D. Sculley. The median h-index is 53 at universities and 19 at frontier AI labs. We compare publishing careers, citations and moves to estimate how universities and frontier labs contribute to AI research.
  3. Google alumni founded or led 87 other organizations, the most among the labs we compareIncludes D. Sculley. We trace 212 organizations founded or led by AI lab alumni, and 223 career moves between the labs.
  4. 44% of AI career moves go from one university to anotherIncludes OpenAI. We estimate how 14,272 AI career moves link universities, companies, labs and government research centers, with net flows and the most common paths.

Colleagues

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

Sources and credits

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

  1. The Making of D. fab.cba.mit.edu. Checked 19 October 2026.
  2. Comp 250: Machine Learning cs.tufts.edu. Checked 19 October 2026.
  3. Dean Carla E. Brodley carla.khoury.northeastern.edu. Checked 19 October 2026.
  4. Web-scale k-means clustering explore.openaire.eu. Checked 19 October 2026.
  5. Machine Learning: The High Interest Credit Card of Technical Debt research.google. Checked 19 October 2026.
  6. Learning to Smell: Using Deep Learning to Predict the Olfactory Properties of Molecules research.google. Checked 19 October 2026.
  7. AIMO Prize Appoints Further Advisory Committee Members aimoprize.com. Checked 19 October 2026.
  8. Safety evaluation competition on OpenAI gpt-oss concluded ndurner.github.io. Checked 19 October 2026.
  9. Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation proceedings.mlr.press. Checked 19 October 2026.