Science in Parallel

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....

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...

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...

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.

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 abou...

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...

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...

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...

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...

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...

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...

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. stud...

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...

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...

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...

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...

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...

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...

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 uncertaint...

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:...

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 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...

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...

Sometimes extraordinary circumstances like the pandemic offer researchers unexpected opportunities to serve others. Danilo P é rez, 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 th...