Science in Parallel
Science in Parallel is a podcast that explores the lives and work of researchers in computational science. Host Sarah Webb interviews scientists about their career paths, motivations, and interdisciplinary research using high-performance computing and artificial intelligence. The show covers topics such as energy challenges, new materials, and medicine modeling. It is produced by the Krell Institute and is part of the Department of Energy Computational Science Graduate Fellowship program.
Episodes
Quantum Quartet (Bonus): DOE CSGF Insights and Career Advice
Recently four alumni of the Department of Energy Computational Science Graduate Fellowship (DOE CSGF) met and discussed quantum science and quantum computing. They also shared how the DOE CSGF helped their careers and their advice for new fellows and other early career computational scientists. To celebrate the 35th anniversary of the DOE CSGF, we've included their answers here as a bonus episode.
S7E4: Quantum Quartet: Insider Insights Toward Fault-Tolerant Systems
Quantum computing involves collaboration and interdisciplinarity, the meeting of minds from different perspectives to solve problems where their expertise overlaps. This episode does a version of that with audio, bringing together insider insights from four quantum researchers across industry, academia and the national labs. They discuss research areas including fundamental quantum mechanics, algo
S7E3: Sam Stanwyck: Quantum Error Correction and Research Partnerships
NVIDIA is known for its AI work, and in quantum computing the company focuses on integrating quantum processors with classical processors to accelerate quantum computing. In this conversation NVIDIA's Sam Stanwyck talks about the challenge and importance of quantum error correction, the company's work on integrating quantum and classical hardware and the partnerships with startup companies and the
S7E2: Megan Ivory: Supporting the Quantum Workforce
Jarrod McClean (Bonus): Parsing Logical Qubits
Quantum computing comes with a new layer of concepts. Quantum bits are called qubits, but there's more. Physical qubits are often grouped to form logical qubits. In our recent conversation with Jarrod McClean, we discussed logical qubits. And we're sharing that discussion as a Science in Parallel short.
S7E1: Jarrod McClean: Designing Quantum Algorithms
In our seventh season, we're putting a spotlight on quantum computing, technology that could help speed up high-performance computing and artificial intelligence, shore up cybersecurity, study complex natural systems and much more. Jarrod McClean works on quantum algorithms and applications at the Google Quantum Artificial Intelligence laboratory, and this conversation links some of the ideas abo
S6E10: Sunita Chandrasekaran: Computation in Translation
Computational science requires translation, breaking ideas and principles into pieces that algorithms can parse. The work requires experts capable of zooming in on core computer science while also being able to step back and make sure that the big scientific questions are addressed. This guest, Sunita Chandrasekaran of the University of Delaware, moves seamlessly across these layers— from working
S6E9: Silvia Crivelli: Understanding Suicide Risk and Building a Foundation Model for Medicine
Nearly a decade ago, the U.S Department of Veterans Affairs and the Department of Energy launched the MVP-CHAMPION initiative, not for sports, but as a data-driven strategy for improving healthcare outcomes for veterans and others. Silvia Crivelli of Lawrence Berkeley National Laboratory turned her skills in computational biology toward this new field, especially the problem of identifying veteran
S6E8:Youngsoo Choi: Building Reliable Foundation Models
Foundation models-- LLMs or LLM-like tools-- are a compelling idea for advancing scientific discovery and democratizing computational science. But there's a big gap between these lofty ideas and the trustworthiness of current models. Youngsoo Choi of Lawrence Livermore National Laboratory and his colleagues are thinking about to how to close this chasm. They're engaging with questions such as: Wha
S6E7: Steven Wilson: Craving Chemical Efficiency
Computational scientists can take on the role of utility players in research, and Steven Wilson is one example. At Arizona State University he's built instruments, carried out experiments and dove deep into computational work. As a postdoc, he's working on a new challenge: building a quantum chemistry startup company. In this episode, he discusses his career that started with 10 years in the Unite
S6E6 [REPOST]: Joe Insley Transforms Big Data into Stunning Images
While we take a short summer break, we're posting one of our favorite past episodes and a great follow-up to our last episode with Amanda Randles of Duke University. In 2023, we talked with Joe Insley of Argonne Leadership Computing Facility and Northern Illinois University about data visualization, from the practical process of helping researchers understand their results to showstopping images a
S6E5: Amanda Randles: A Check-Engine Light for the Heart
Duke University associate professor Amanda Randles' work to simulate and understand human blood flow and its implications demonstrates how high-performance computing paired with scientific principles can help improve human health. In this conversation, she talks about how she brought together early interests in physics, coding, biomedicine and even political science and policy and followed her ent
S6E4: Joel Ye: Examining Neural Data More Efficiently and Holistically
Understanding how the brain works remains a grand scientific challenge, and it's yet another area where researchers are examining whether foundation models could help them find patterns in complex data. Joel Ye of Carnegie Mellon University talks about his work on foundation models, their potential and limitations and how others can get involved in applying these AI tools. Joel Ye is a Ph.D. stude
S6E3: Jackson Burns: Avoiding Chemical Dead Ends
Chemists and chemical engineers have modeled molecules for decades, but artificial intelligence and foundation models offer the prospect that researchers could train models with predictive abilities in one area of chemistry that could be fine-tuned for another. Trustworthy chemistry foundation models could help streamline the experimental time and resources needed to discover new medicines or desi
S6E2: Prasanna Balaprakash: Predicting Earth Systems and Harnessing Swarms for Computing
In the second episode in our series on foundation models for science, we discuss Oak Ridge National Laboratory's work and hear about lessons learned from the recent 1000 Scientists AI Jam, a recent event that brought together researchers from several Department of Energy national laboratories, OpenAI and Anthropic. My guest is Prasanna Balaprakash, ORNL's director of AI programs. We talk about how
S6E1 - Ian Foster: Exploring and Evaluating Foundation Models
Large language models aren't just powering chatbots like ChatGPT. This type of computational model is an example of a particular flavor of artificial intelligence known as foundation models, which are trained on vast amounts of data to make inferences in new areas. Although text is one rich data source, science offers many more from biology, chemistry, physics and more. Such models open up a tanta
S5E7 - Computational Scientists Discuss 2024 Nobel Prizes
Wrapping up our discussion of the 2024 Nobel Prizes in Physics and Chemistry, computer scientist Mansi Sakarvadia and computational structural biologist Josh Vermaas talk about the recent prizes and what they mean for science. You'll hear about how the prizes both break down research barriers and introduce concerns about misinformation and public trust. The research honored with the chemistry priz
S5E6 - Anil Ananthaswamy: AI's Nobel Moment
2024 was artificial intelligence's Nobel Prize year with the physics and chemistry prizes recognizing the underpinnings and application of these algorithms. Science journalist and author Anil Ananthaswamy spent years writing a popular book, Why Machines Learn: The Elegant Math Behind Modern AI, that explores the equations and historical context for this technology. In this conversation, Anil and h
S5E5 - Sadie Bartholomew: Patterns in Computing and Art
The annual Supercomputing meeting (SC24) convenes November 17-22 in Atlanta with the theme of HPC creates, and Science in Parallel previews a special display at the meeting: the Art of HPC. Host Sarah Webb interviews Sadie Bartholomew of the United Kingdom's National Centre for Atmospheric Science and the University of Reading about her work as a research software engineer and her passion for cre
S5E4 - Paulina Rodriguez: Building Credibility and Authenticity
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
S5E3 - Paul Sutter the Spaceman: Adventures in Science and Outreach
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:
S5E2 - Rogelio Cardona-Rivera Plays Games for Science
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.
S5E1 - Lois Curfman McInnes: Building Software Sustainability and Broadening Workforce Participation
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. 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'l
S4E4 - Anubhav Jain: Hacking Materials
Artificial intelligence is reshaping research to discover new materials for a range of important applications. In this episode, meet Anubhav Jain 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 o
Season 4, Episode 3 -- Danilo Pérez: Embracing Versatility
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
Season 4, Episode 2 -- Casey Berger: Choose Your Own Multidimensional Career
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
Season 4, Episode 1 -- Creativity in Climate Modeling
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
Season 3, Episode 5 -- Beyond Exascale: Exploring Emerging Hardware
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: L
Season 3, Episode 4 -- Gabriel Casabona: It All Comes Down to Gravity
Although he's always loved space, Gabriel Casabona pursued other fields, including medicine and religion, before landing in astrophysics. We discussed how his passion for physics motivated him to deepen his knowledge of math and computing, how gravity's mysteries define his work and other big challenges he hopes to work on during his career. You'll meet: Gabriel Casabona is a Ph.D. student in comp
Season 3, Episode 3 -- Tammy Ma: Fusion Ignition and Beyond
In early December 2022, Lawrence Livermore National Laboratory announced that the National Ignition Facility (NIF) had achieved fusion ignition—a reaction of merging hydrogen isotopes that produced more energy than the lasers put in. High-performance computing is an important part of designing, analyzing and refining these experiments, and this episode examines the connection between computing and
Season 3, Episode 2 –- Margaret Lawson: Finding Her Place
Even after enjoying her first computer science course, Margaret Lawson wasn't convinced she'd have a place in the field. But today she works on cloud storage for Google after completing her Ph.D. at the University of Illinois, Urbana-Champaign, where she was supported by a Department of Energy Computational Science Graduate Fellowship (DOE CSGF). This conversation was recorded at the Supercomputin
Season 3, Episode 1 -- Joe Insley: Big Data to Beautiful Images
Making sense of computational science takes a multidisciplinary team, including science visualization experts who translate data into images that both parse information so that it's comprehensible and render it into beautiful images and skillful animations. Joe Insley of Argonne Leadership Computing Facility and Northern Illinois University has been doing this work for more than 20 years, leveragi
Season 2, Episode 6 -- Pushing Limits in Computing and Biology
Science in Parallel's season two concludes with a conversation about answering important questions in biology and medicine with leadership class supercomputers, including urgent issues that came up during the COVID-19 pandemic. You'll hear from Anda Trifan of the University of Illinois, Urbana-Champaign and Amanda Randles of Duke University. Starting as a chemist, Anda is completing a Ph.D. in bio
Season 2, Episode 5 -- Improving Computing Performance and Workforce Diversity
Valerie Taylor doesn't shy away from challenging problems with multiple layers. At Argonne National Laboratory, she manages teams that develop algorithms, data management strategies, software and hardware to support scientific simulations, including those on the Department of Energy's leadership-class supercomputers. Her research focuses on performance analysis—the factors involved in making compu
Season 2, Episode 4 -- You're Moving to Finland?
After COVID-19 lockdowns and 2020 wildfires near his Oregon home, computational scientist Jeff Hammond decided to make big moves. In 2021, his family of five emigrated from Portland to Finland, and Jeff changed positions, leaving Intel and taking a new job with NVIDIA. Even before 2020, he had worked primarily remotely and discusses the lessons he hopes technology companies learn from pandemic wor
Season 2, Episode 3 -- Two PhDs + Pandemic + Baby
Pandemic work was especially challenging for computational scientist parents, who often juggled new work arrangements while balancing their children's care. In this episode you'll hear from a couple who were Ph.D. students and had a 10-month-old baby when lockdowns sent them all home in March 2020. The situation challenged their work and their mental health. As they adapted to these experiences, t
Season 2, Episode 2 -- Future of Work (part 2): Adapting to Change
In Season 2 of Science in Parallel, we're examining how pandemic shutdowns have reshaped computational science workplaces. In our last episode we focused on the effects of virtual work and how the Exascale Computing Project's Strategies for Working Remotely panel series fostered communication and creativity. This episode brings in additional stories from graduate students, a professor and an early
Season 2, Episode 1 -- Future of Work (part 1): Communication Conundrum
In our first two episodes of Science in Parallel's Season 2, we'll be talking about how the pandemic pivot to remote work marks a turning point in workplace structure for many computational scientists. We talk with computational scientists who worked remotely about what they struggled with, what functioned well and the lessons they'll take into the future. In this first part, we'll also focus on
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 Unive
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 cho
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
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
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.
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
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 t
