PeopleofSuperintelligence

Researcher

Matthias Seeger

Matthias Seeger is a machine-learning researcher whose work spans Gaussian-process optimization, hyperparameter search and long-context sparse attention. He earned a computer-science diploma at Karlsruhe University and a PhD at Edinburgh, then held research posts at Berkeley and Max Planck and a faculty role at EPFL before joining Amazon in 2014. His GP-UCB paper received the 2020 ICML Test of Time Award, and he coauthored Syne Tune for distributed hyperparameter optimization and a 2024 paper on model explanations. As of October 2026, he is a Principal Machine Learning Scientist at Amazon.

Now at
Amazon
Badges

Timeline

  1. 1999–2003

    A Karlsruhe diploma and Edinburgh PhD

    He earns a computer-science diploma from Karlsruhe University in 1999 and completes a PhD at the University of Edinburgh's School of Informatics in 2003, supervised by Christopher Williams.

  2. 2003–2010

    Research posts at Berkeley and EPFL

    From 2003, he is a research fellow with Michael Jordan and Peter Bartlett at the University of California, Berkeley; from 2005, he works with Bernhard Schoelkopf at the Max Planck Institute for Intelligent Systems in Tuebingen. He leads a research group at the University of Saarbruecken from 2008, and EPFL appoints him a Tenure Track Assistant Professor of Information Technology in October 2010 while he leads an independent group at the Max Planck Institute for Informatics at Saarland University.

  3. 2010

    A paper on Gaussian-process bandits

    In 2010, he coauthors “Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design” with Niranjan Srinivas, Andreas Krause and Sham M. Kakade. The paper analyzes GP-UCB and derives regret bounds that connect Gaussian-process optimization with experimental design.

  4. 2014–2020

    Amazon role and ICML award

    He joins Amazon as a machine-learning scientist in 2014. In 2020, ICML gives his 2010 GP-UCB paper the Test of Time Award.

  5. 2021

    Syne Tune for hyperparameter search

    In November 2021, he coauthors AWS’s announcement for Syne Tune, an open-source Python library for large-scale distributed hyperparameter and neural-architecture optimization.

  6. 2024

    Explaining probabilistic models

    In 2024, he coauthors “Explaining probabilistic models with distributional values,” a machine-learning paper on why game-theoretic methods such as SHAP can be difficult to interpret.

  7. 2025–2026

    Amazon Q Developer and sparse attention

    In January 2025, he coauthors an AWS article about diagnosing errors in the AWS Console with Amazon Q Developer. In 2026, he coauthors “Learning how to Forget: Fine-tuning for Long-Context Sparse Attention” with Zeyu Zhang, Vihang Patil, Konstantinos Benidis and Sebastian Schelter.

  8. As of October 2026

    Principal scientist at Amazon

    As of October 2026, he is a Principal Machine Learning Scientist at Amazon.

Career

  1. Since 2014AmazonMachine-learning scientist
  2. From 2010EPFLTenure Track Assistant Professor of Information Technology
  3. From 2008Saarland UniversityResearch Group Leader
  4. From 2005Max Planck Institute for Intelligent Systems
  5. 2003–2005University of California, BerkeleyResearch Fellow
  6. Max Planck Institute for InformaticsResearch Group Leader

Education

  1. 2003University of EdinburghPhD
  2. 1999Karlsruhe UniversityDiploma

From the biography.

  1. 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 Amazon. 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.
  2. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Amazon. 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.
  3. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes Amazon. 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.
  4. 22 of 133 people shaping AI with a former OpenAI role now work at AnthropicIncludes Amazon. 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.

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. Matthias Seeger mseeger.github.io. Checked 21 October 2026.
  2. DAGM 2010 conferences.mpi-inf.mpg.de. Checked 21 October 2026.
  3. Two IC Professors appointed by EPF Board of Directors - EPFL actu.epfl.ch. Checked 21 October 2026.
  4. Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design arxiv.org. Checked 21 October 2026.
  5. Amazon scientist Matthias Seeger receives ICML "test of time" award amazon.science. Checked 21 October 2026.
  6. Awards: Test of Time and Best Papers icml.cc. Checked 21 October 2026.
  7. Run distributed hyperparameter and neural architecture tuning jobs with Syne Tune aws.amazon.com. Checked 21 October 2026.
  8. Matthias Seeger - Amazon Science amazon.science. Checked 21 October 2026.
  9. Unlocking AWS Console: Diagnosing Errors with Amazon Q Developer aws.amazon.com. Checked 21 October 2026.
  10. Learning how to Forget: Fine-tuning for Long-Context Sparse Attention arxiv.org. Checked 21 October 2026.