Season 1, Episode 2 -- Artificial Intelligence and Climate Change
Release Date: 07/15/2021
S5E5 - Sadie Bartholomew: Patterns in Computing and Art
Science in Parallel
The annual convenes November 17-22 in Atlanta with the theme of HPC creates, and Science in Parallel previews a special display at the meeting: . Host Sarah Webb interviews Sadie Bartholomew of the United Kingdom's and the about her work as a research software engineer and her passion for creative coding. She submitted several pieces of digital art that will be displayed at SC24. Sadie discussed the many patterns in her work—within weather and climate, in coding and in digital art. She makes her pieces using matplotlib, a visualization tool in Python. She talks about the synergy and...
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S5E4 - Paulina Rodriguez: Building Credibility and Authenticity
Science in Parallel
Early in her applied math journey, Paulina Rodriguez was a little skeptical of calculators and computers. But her desire to really understand what’s going on under the hood has ultimately led to satisfying research. During her Ph.D., she’s explored the credibility of computational models for medical device applications, making sure that researchers understand the accuracy, validity and uncertainty of simulated results. Paulina shares how she honed her problem-solving skills and creativity as she navigated her education. Her enthusiasm and determination are infectious, and she describes her...
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S5E3 - Paul Sutter the Spaceman: Adventures in Science and Outreach
Science in Parallel
Science communication often attracts people with diverse interests, who thrive in multiple roles. Paul Sutter is no exception: he’s an astrophysicist, host, author and more. He’s also a visiting professor at Barnard College, Columbia University. Paul’s roots are in computational science, and he shares how his many projects continue to build on that foundation. We also discuss his most recent book: Rescuing Science: Restoring Trust in an Age of Doubt, which critiques today’s scientific enterprise and and offers ideas for supporting a better future. You'll meet: is a theoretical...
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S5E2 - Rogelio Cardona-Rivera Plays Games for Science
Science in Parallel
Video games are everywhere, but the fundamental elements that generate human reactions such as suspense or surprise aren’t understood. Instead, game designers start from scratch each time they want to build a new experience for players. Rogelio Cardona-Rivera of the University of Utah wants to understand games and the fundamental elements that make people respond as they do—as a science of games. The research is important for more than just gaming—Rogelio is working on a variety of projects, including artificial intelligence research, technology for Indigenous storytelling and virtual...
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S5E1 - Lois Curfman McInnes: Building Software Sustainability and Workforce Diversity
Science in Parallel
The field of high-performance computing (HPC) currently faces dual challenges: important technical problems that require a skilled workforce and the need to recruit more computational researchers, especially those from underrepresented communities. This conversation with Lois Curfman McInnes of Argonne National Laboratory examines both the complexity in building scientific software and the work needed to build the HPC workforce of the future. You'll meet: is a senior computational scientist in the mathematics and computer science division at . She served as deputy director for the software...
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S4E4 - Anubhav Jain: Hacking Materials
Science in Parallel
Artificial intelligence is reshaping research to discover new materials for a range of important applications. In this episode, meet of Lawrence Berkeley National Laboratory, a researcher who has been at the forefront of this transition. He uses machine learning and other computational tools as a materials scientist to discover compounds that could store and convert energy and solve other societal problems. Anubhav’s current research path started in graduate school at MIT, where he was supported by a . We discuss how computational tools including AI have moved from a novel idea to a central...
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Season 4, Episode 3 -- Danilo Pérez: Embracing Versatility
Science in Parallel
Sometimes extraordinary circumstances like the pandemic offer researchers unexpected opportunities to serve others. Danilo Pérez, now a Ph.D. student in computational neuroscience at New York University, found himself in this situation in Puerto Rico in 2020. He contributed his mathematical modeling expertise as part of a team that built and maintained Puerto Rico’s public health data during that intense period. Later he contributed to AI-based modeling of coronavirus variants that won major honors in the computing community: the 2022 Gordon Bell Special Prize for HPC-Based COVID-19...
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Season 4, Episode 2 -- Casey Berger: Choose Your Own Multidimensional Career
Science in Parallel
Traditional science career advice often urges people to specialize and become the best at one activity. But that perspective can undervalue interdisciplinary researchers and other polymaths who can see connections between and beyond science and engineering fields. This episode’s guest, Casey Berger, describes how she has navigated this second approach, embracing her many interests, such as science, computing, teaching and storytelling, to make her mark as a physicist and data scientist and as a fiction author. In the second episode of our podcast series on creativity in computing, Casey...
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Season 4, Episode 1 -- Creativity in Climate Modeling
Science in Parallel
Season 4 of Science in Parallel centers around creativity and computing, starting with an interview about climate modeling. At this nexus of physics, earth science, mathematics and computing, researchers are also racing against the clock to accurately predict how global climate is shifting before the changes happen. Pulling all the scientific pieces together and communicating those results so that others can use them are significant creative challenges—ones that both Tapio Schneider and Emily de Jong of California Institute of Technology have embraced. In our conversation, Tapio and Emily...
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Season 3, Episode 5 -- Beyond Exascale: Exploring Emerging Hardware
Science in Parallel
The exascale era in computing has arrived, and that brings up the question of what’s next. We’ll discuss some emerging processor technologies-- molecular storage and computing, quantum computing and neuromorphic chips—with an expert from each of those fields. Learn more about these technologies’ strengths and challenges and how they might be incorporated into tomorrow’s systems. You’ll meet: , professor of and CEO of the AI startup . , senior scientist and department head for computational sciences at and deputy director of the . , is a neuromorphic computing...
info_outlineOne 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.