PeopleofSuperintelligence

Researcher

Benjamin Hillman

Also known as Benjamin R. Hillman

Benjamin Hillman researches machine learning for climate simulation and analysis. He studied physics and mathematics at Western Washington University, then atmospheric sciences at the University of Washington, where he compared model clouds with satellite observations. At Sandia National Laboratories, he is technical staff in Atmospheric Science / Climate Systems and contributes to the Department of Energy's Energy Exascale Earth System Model. He coauthored ClimSim, a hybrid physics-ML climate dataset that won a NeurIPS Outstanding Paper award in 2023; his later research applies machine-learning feature importance to Earth system models and examines volcanic aerosol effects in E3SMv2.

Timeline

  1. 2005–2016

    Degrees in physics and atmospheric science

    He earns an A.S. at Shoreline Community College in 2005 and a B.S. in physics and mathematics at Western Washington University in 2008. At the University of Washington, he completes an M.S. in atmospheric sciences in 2012 and a Ph.D. in 2016, working with Thomas Ackerman and Roger Marchand on cloud-evaluation methods.

  2. 2008–2016

    Graduate research at Washington

    He works as a graduate research associate in the University of Washington's Department of Atmospheric Sciences from 2008 to 2016, evaluating cloud properties in atmospheric models against satellite retrievals with instrument simulators.

  3. 2016–2017

    Postdoctoral appointee at Sandia

    At Sandia's Department of Atmospheric Science, he serves as a postdoctoral appointee from 2016 to 2017, studying Arctic cloud processes with high-resolution atmospheric modeling and observations.

  4. 2018

    Simulated satellite views of clouds

    In 2018, he publishes a study on how subgrid-scale overlap and condensate heterogeneity affect simulated satellite views of clouds.

  5. 2023

    The cloud-resolving E3SM on Frontier

    He coauthors a 2023 paper on the Simple Cloud-Resolving E3SM Atmosphere Model running on Frontier, a key part of the Department of Energy's Energy Exascale Earth System Model.

  6. 2023

    ClimSim for hybrid climate emulation

    He coauthors the 2023 ClimSim paper, which presents a multi-scale dataset for hybrid physics-ML climate emulation and receives an Outstanding Paper award from NeurIPS. A related ClimSim-Online preprint submitted in 2023 adds an end-to-end workflow for developing hybrid ML-physics simulators.

  7. 2025

    Machine learning for climate analysis

    In 2025, he coauthors a study applying spatiotemporal zeroed feature importance to examine climate-variable relationships across Earth system model ensembles. The analysis traces climate effects from aerosols to radiation and temperature after the 1991 Mount Pinatubo eruption.

  8. 2017–2026

    Technical staff at Sandia

    In 2017, he becomes technical staff in Sandia's Department of Atmospheric Science / Climate Systems and works on the Department of Energy's Energy Exascale Earth System Model. In 2026, he coauthors a paper on volcanic aerosol effects on E3SMv2's stratospheric circulation.

Career

  1. 2016–2026National Nuclear Security AdministrationPostdoctoral appointee, Technical staff
  2. 2008–2016University of WashingtonGraduate research associate

Education

  1. 2016University of WashingtonPh.D.
  2. 2012University of WashingtonM.S.
  3. 2008Western Washington UniversityB.S.
  4. 2005Shoreline Community CollegeA.S.

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 Benjamin Hillman. 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. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Washington. 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.
  3. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Washington. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  4. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes University of Washington. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.

Colleagues

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

Sources and credits

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  1. Cirriculum Vitae | Benjamin R. Hillman brhillman.github.io. Checked 20 October 2026.
  2. NeurIPS 2023 Awards neurips.cc. Checked 20 October 2026.
  3. [2306.08754] ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation arxiv.org. Checked 20 October 2026.
  4. GMD - Using feature importance as an exploratory data analysis tool on Earth system models gmd.copernicus.org. Checked 20 October 2026.
  5. Publications & Presentations – CLDERA sandia.gov. Checked 20 October 2026.