News Release

Updating the way the Lab computes

Shantenu Jha, a computer engineering expert with an interest in artificial intelligence, appointed head of PPPL’s Computational Sciences Department

Business Announcement

DOE/Princeton Plasma Physics Laboratory

Shantenu Jha

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Shantenu Jha, the new head of computational sciences at Princeton Plasma Physics Laboratory. 

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Credit: Photo credit: Michael Livingston / PPPL Communications Department

Unraveling the behavior of plasma increasingly requires intensive computing resources. That’s why plasma demands a calculated approach to computation. 

As the new head of computational sciences at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), Shantenu Jha is excited to be at the helm of the Lab’s computing efforts, fusing computer science expertise with PPPL’s pioneering research into the fourth state of matter.

“I want to continue to grow the excellence that already exists in computing for fusion energy at PPPL, which is arguably the best in the world,” he said. 

Most recently, Jha was the chair of the Computation and Data-Driven Discovery Division at Brookhaven National Laboratory. He is also a computer engineering professor at Rutgers University and will continue to work there. Jha is a leading expert in computer engineering, and his research interests are at the intersection of high-performance distributed computing and computational and data-driven science.

“Shantenu is an ideal fit for PPPL, given his recent experience supporting the growth of a new computational science core capability at a larger national laboratory,” said Jon Menard, deputy director for research and chief research officer at PPPL. “It’s also an ideal time for him to join the Lab, as his knowledge of machine learning and workflow management on exascale computers will directly support our push to develop advanced computational tools for next-step fusion device design, such as stellarator and spherical tokamak fusion pilot plants.”

Speaking in a soft, well-metered and deliberate tone that highlights his attention to detail, Jha said he hopes to build PPPL’s core capabilities in computational science, bridge computational efforts between the Princeton University campus and the Lab, and take advantage of the exciting opportunities in artificial intelligence (AI) and high-performance computing. 

“I think the thing that excited me is the opportunity to build a program in computing that will serve the Lab as it goes from a single mission to a multiprogram lab that includes research in a variety of areas, including sustainability and materials chemistry,” Jha said. “Our goal is to bridge connections between the Lab and University so we’re doing this collectively.” 

Jha wants to help the department grow its capabilities in computational science in several ways. On the top of his list is growing excellence in computing by hiring computer science specialists. “We want to bring more specialists — computer scientists — who can bring the best of the computer science that exists in other domains like materials, biology and other parts of physics and apply those advanced computing techniques and capabilities to fusion energy,” he said. 

Jha also wants to bridge computational efforts between Princeton University and the Lab for a more coherent approach. This will help PPPL remain on the leading edge of physics while using the most appropriate computer science approaches. It will also ensure the Lab understands the nuances of the future computing landscape. To build core computer science research capability expertise, Jha will also work to strengthen the Lab’s applied math and computational science research. 

There’s also a clear need to combine high-performance computing with AI to solve scientific problems. “I’m a bit biased because I’ve been working in this area, but I think AI and high-performance computing for science might be some of the most important changes in the scientific methodology. We need to bring AI and high-performance computing together to advance many of the scientific disciplines,” he said.

In addition to using AI to develop next-generation fusion reactors, including stellarators, Jha sees great value in using AI to deepen our understanding of plasma with more accuracy, in more granular levels of detail in terms of both time and space, as well as the way plasma behaves over longer periods of time. “There are some AI approaches that allow us to solve partial differential equations better and faster, without loss of accuracy,” Jha said.

Jha has a master’s degree in physics from the Indian Institute of Technology Delhi, as well as a master’s degree and a doctorate in computer science from Syracuse University. In 2016, Jha received the Chancellor’s Excellence in Research award for his work on cyber infrastructure work. This is the highest award for research contributions bestowed to Rutgers faculty. He is also a recipient of the Institute of Electrical and Electronics Engineers’ International Scalable Computing Challenge (SCALE) 2018 award and the National Science Foundation’s Faculty Early Career Development Program award. In 2020, Jha won one of the top awards in high-performance computing, the Association for Computing Machinery Gordon Bell Prize. 

While Jha used to enjoy running outdoors and biking, his favorite hobby lately is reading about developmental economics. “I like trying to understand how economic decisions influence society,” Jha said.

PPPL is mastering the art of using plasma — the fourth state of matter — to solve some of the world's toughest science and technology challenges. Nestled on Princeton University’s Forrestal Campus in Plainsboro, New Jersey, our research ignites innovation in a range of applications including fusion energy, nanoscale fabrication, quantum materials and devices, and sustainability science. The University manages the Laboratory for the U.S. Department of Energy’s Office of Science, which is the nation’s single largest supporter of basic research in the physical sciences. Feel the heat at https://energy.gov/science and https://www.pppl.gov


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