PeopleofSuperintelligence

Builder

Robert Kern

Also known as rkern

Robert Kern is a scientific Python developer who maintains NumPy and works on SciPy, and 47% of all machine learning projects on GitHub use SciPy. As an undergraduate student, he wrote Windows compilation instructions for Multipack, an early package that the SciPy project absorbed. NumPy's reproducible random-number policy dates from November 2008, and in 2018 he wrote NumPy Enhancement Proposal 19, which proposed relaxing it. In 2020, he coauthored the SciPy 1.0 paper in Nature Methods and "Array programming with NumPy" in Nature. He is Corporate Vice President and Principal Scientist at Enthought, holds a B.S. in geophysics from the California Institute of Technology, and wrote the original line_profiler package.

Now at
Enthought

Timeline

  1. By 2001

    Windows help for Multipack

    As an undergraduate student, he provides compilation instructions under Windows for Multipack, a set of extension modules that wrap Fortran and C libraries for nonlinear equations, least-squares problems, differential equations and splines. Eric Jones and Travis Vaught found Enthought in 2001 and create the SciPy project, which subsumes Multipack and the other early packages.

  2. 2008

    Reproducible random numbers in NumPy

    NumPy first instates its random-number policy in November 2008: a fixed seed and a fixed series of RandomState calls always produce the same results up to roundoff error. He is the maintainer who made the compatibility promises behind it, and NumPy's contributor credits thank him for mtrand, bug fixes, distutils help, code organization and strided tricks.

  3. 2018

    NumPy Enhancement Proposal 19

    In 2018, he writes NumPy Enhancement Proposal 19, which proposes relaxing the strict stream-compatibility policy so that faster or more accurate algorithms can enter NumPy's random number distributions. The proposal sketches separate core generators called BitGenerators and a Generator class for the distributions, and it reaches Final status.

  4. February 2020

    Coauthor of the SciPy 1.0 paper

    In February 2020, he is a coauthor of "SciPy 1.0: fundamental algorithms for scientific computing in Python" in Nature Methods, listed at Enthought. He is a SciPy core developer, and SciPy is used by 47% of all machine learning projects on GitHub.

  5. September 2020

    Coauthor of the NumPy paper

    In September 2020, he is a coauthor of "Array programming with NumPy" in Nature, which presents NumPy as the primary array programming library for Python. The article notes that the growth of data science, machine learning and artificial intelligence has boosted the scientific use of Python.

  6. As of October 2026

    Principal Scientist at Enthought

    He is Corporate Vice President and Principal Scientist at Enthought, and NumPy lists him among its maintainers. His degree is a B.S. in geophysics from the California Institute of Technology, with advanced training in geophysics from the Scripps Institution of Oceanography. The original line_profiler package, a module for line-by-line profiling of functions, is his work.

Career

  1. NowEnthoughtCorporate Vice President and Principal Scientist

Education

  1. California Institute of TechnologyB.S. in geophysics

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes California Institute of Technology. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. People shaping AI work at a median of 3 organizations over a career: 3 for university starters and institute and lab starters, versus 2 for company startersIncludes California Institute of Technology. Across 6,853 people shaping AI with a dated work role, we estimate a median of 3 parent organizations over a career (mean 3.6), comparing role groups, starting sectors and starting decades from the 1950s to 2020–2026.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes California Institute of Technology. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes California Institute of Technology. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.

Sources and credits

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

  1. SciPy 1.0: fundamental algorithms for scientific computing in Python | Nature Methods nature.com. Checked 22 October 2026.
  2. NEP 19 — Random number generator policy — NumPy Enhancement Proposals numpy.org. Checked 22 October 2026.
  3. THANKS.txt - external/github.com/numpy/numpy - Git at Google chromium.googlesource.com. Checked 22 October 2026.
  4. Array programming with NumPy | Nature nature.com. Checked 22 October 2026.
  5. Meet The Team | Enthought enthought.com. Checked 22 October 2026.
  6. NumPy - NumPy Teams numpy.org. Checked 22 October 2026.
  7. line-profiler · PyPI pypi.org. Checked 22 October 2026.
  8. rkern (Robert Kern) · GitHub github.com. Checked 22 October 2026.