Science in Parallel

Science in Parallel

By Krell InstituteScienceTechnology
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Science in Parallel episodes

  • Season 1, Episode 6 -- Aurora Pribram-Jones

    Aurora Pribram-Jones works on hot, dense electrons – simulating extreme chemistry that can happen within giant planets like Jupiter or nuclear fusion experiments. Aurora's career included many initial detours on the way to science, but the flexibility of community college classes and a job at a technical bookstore paved their path toward research. Now a member of the chemistry faculty at the University of California, Merced, Aurora finds purpose in teaching and mentoring students and supporting the whole scientist.

    Aurora completed a Ph.D. at the University of California, Irvine, and was a DOE CSGF recipient from 2011 to 2015. They carried out postdoctoral research at the University of California, Berkeley, and at Lawrence Livermore National Laboratory, the latter supported by a Lawrence Postdoctoral Fellowship. Aurora received the Frederick A. Howes Scholar Award in Computational Science in 2016.

    28 min
  • Season 1, Episode 5 -- Alternative Energy

    Avoiding the changing climate's most extreme impacts will require a technological revolution to power daily life from renewable sources. An entrepreneur, an engineering professor and a DOE-laboratory materials scientist – all DOE CSGF and Massachusetts Institute of Technology alumni – discuss technical challenges from nuclear energy to heat transfer to hydrogen generation and the importance of choosing high-impact research problems. In addition to talking about science, engineering and computation, they highlight the need for a strong social and political movement to drive a complete overhaul of our energy infrastructure.

    You'll meet:

    Leslie Dewan is a nuclear engineering entrepreneur and venture capitalist, who is currently the CEO of RadiantNano, a startup focused on radiation detection, identification and imaging.

    Asegun Henry is an MIT associate professor of mechanical engineering. What he calls his "sun in a box" design could lead to a viable system for storing renewable energy for the electrical grid.

    Brandon Wood is the associate program lead for Hydrogen and Computational Energy Materials at Lawrence Livermore National Laboratory and deputy director of the Laboratory for Energy Applications for the Future (LEAF).

    39 min
  • Season 1, Episode 4 -- Alicia Magann

    Alicia Magann got her start in control systems engineering research, exploring tools for controlling large-scale chemical processes. As a Ph.D. student, she turned the dials of quantum chemistry in Herschel Rabitz's research group at Princeton University with support from the DOE CSGF. She talks about her work on quantum algorithms, her cross-country road trip from New Jersey to her practicum in California and how her dad is her scientific hero.

    Read more about Alicia and her work in the 2021 issue of DEIXIS.

    20 min
  • Season 1, Episode 3 -- Quentarius Moore

    Curiosity, mentors and a summer working in concrete with his grandfather shaped Quentarius Moore's science career studying 2-D materials. He recently completed his fourth year as a DOE CSGF recipient, while pursuing a chemistry Ph.D. at Texas A&M University. He completed both his bachelor's and master's degrees in chemistry at Jackson State University in Mississippi. Read more about Quentarius and his graduate research in the 2021 issue of DEIXIS magazine.

    34 min
  • Science in Parallel -- Season One Trailer

    Welcome to Science in Parallel, a new podcast about people and projects in computational science. Science in Parallel is produced by the Krell Institute, and season one celebrates the 30th anniversary of the Department of Energy Computational Science Graduate Fellowship Program.

    1 min
  • Season 1, Episode 2 -- Artificial Intelligence and Climate Change

    One of today's hottest areas of computational research could help build better solutions for one of global society's steepest challenges. Three early career computational scientists talk about AI's potential for understanding and predicting climate shifts, supporting strategies for incorporating renewable energy, and engineering other approaches that reduce carbon emissions. They also describe how AI can be misused or can perpetuate existing biases.

    Working at this important research interface requires broad knowledge in areas such as climate science, public policy and engineering coupled with computational science and mathematics expertise. These early career researchers talk about their approaches to bridging this gap and offer their advice on how to become a scientific integrator.

    You'll meet:

    Priya Donti is a Ph.D. student at Carnegie Mellon University, pursuing a dual degree in public policy and computer science, and a 4th year DOE CSGF recipient. She is also a co-founder and chair of the volunteer organization, Climate Change AI, which provides resources and a community for researchers interested in applying artificial intelligence to climate challenges. Priya was named to MIT Technology Review's 2021 list of Innovators Under 35. Read more about Priya and her work in the 2021 issue of DEIXIS.

    Kelly Kochanski completed a Ph.D. in geological sciences at the University of Colorado, Boulder in 2020 and works as a senior data scientist in climate analytics at McKinsey & Company. Kelly was a DOE CSGF recipient from 2016 to 2020, and her graduate research was featured in the 2020 issue of DEIXIS. She also is profiled in the 2021 issue as one of this year's recipients of the Frederick A. Howes Scholar Award.

    Ben Toms also finished his Ph.D. last year at Colorado State University studying atmospheric science and is a 4th year DOE CSGF recipient. He has founded a company, Intersphere, that provides weather and climate forecasts up to a decade into the future.

    From the episode:

    • Kelly and Priya contributed to the review article: Tackling Climate Change with Machine Learning, which was published on the arXiv preprint server in 2019.
    • In the discussion about interpretable AI, Priya mentioned an article by Cynthia Rudin: Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.
    • Ben mentioned Vulcan's work to build faster climate change models.
    34 min
  • Season 1, Episode 1 -- Jeff Hittinger

    Jeff Hittinger of Lawrence Livermore National Laboratory embodies the term scientist-chimera. He talks about the many scientific hats he's worn simultaneously – computer scientist, applied mathematician and physicist. As director for the Center for Applied Computing (CASC) and as co-principal investigator for the DOE CSGF, he wears many more. He talks about scientific success, leadership and the tricks he's cultivated for communicating science to broader audiences through the Livermore Ambassador Lecture series.

    Jeff was a DOE CSGF recipient from 1996 to 2000 while earning his Ph.D. in aerospace engineering and scientific computing at the University of Michigan. He was one of the first recipients of the Frederick A. Howes Scholar Award and received the 2021 James Corones Award in Leadership, Community Building and Communication.

    32 min

About Science in Parallel

From the publisher's feed

Science in Parallel focuses on people in computational science and their interdisciplinary research to solve energy challenges, discover new materials, model medicines and more — using high-performance computing (HPC) and artificial intelligence. Host Sarah Webb interviews researchers about their career paths and motivations. Our conversations cover topics such as integrating emerging hardware, the effects of remote work, the role of creativity in computing and foundation models in science.