William Tang, a principal research physicist at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) for five decades and a lecturer with the rank of professor in the Department of Astrophysical Sciences at Princeton University, has won the 2024 Sidney Fernbach Memorial Award from the Institute of Electrical and Electronics Engineers (IEEE) Computer Society. The IEEE is the world’s largest technical professional organization “dedicated to advancing technology for the benefit of humanity.”

The IEEE Computer Society announced the award on Oct. 30, and Tang will receive it at the Supercomputing 2024 (SC24) Conference in Atlanta on Nov. 19 “for pioneering contributions to fusion energy research accelerated by high-performance computing and deep learning.” The award includes a $2,000 honorarium. 

“Receiving this award is really very gratifying,” Tang said. “It acknowledges the importance of the work that’s been done and the fact that it is really a 21st-century award in that it highlights the major growth area of artificial intelligence (AI) and deep learning. This is, in fact, the research in which I am very actively involved.”
 

A founder of the Princeton Institute for Computational Science and Engineering

Tang was one of the founders of the Princeton Institute for Computational Science and Engineering (PICSciE). He served as associate director from 2003 to 2009 with Jeremiah Ostriker, who was the director at that time. Tang is currently a member of the executive team. He was a principal investigator for the Intel Parallel Computing Center of Excellence at PICSciE from 2014 to 2018. 

Tang joined PPPL in 1972 after receiving his graduate degree in physics from the University of California-Davis with doctoral research carried out at the Lawrence Livermore National Laboratory. In his early days at PPPL, he met and closely interacted with some of the founders of plasma physics at the Lab, including Marshall Rosenbluth, who was at the Institute for Advanced Study; Edward Frieman, the deputy director; and Thomas Stix. 

Stix, who founded the Princeton Program in Plasma Physics, recruited Tang to join the graduate program as a lecturer more than 40 years ago. He co-taught classes with Rosenbluth, Stix and especially physicist Russell Kulsrud. Among the many students in his classes were Steve Cowley, now the Laboratory director, and Principal Research Physicist Greg Hammett. He also supervised graduate students Zhihong Lin, now Chancellor’s Professor of Physics at the University of California-Irvine, and Hong Qin, now his colleague at both PPPL and Princeton University — who won the Presidential Early Career Award for Scientists and Engineers in 2000 and 2004, respectively.
 

Former head of the Theory Department and chief scientist at PPPL 

Tang was head of the Theory Department from 1992 to 2004 and chief scientist at PPPL from 1997 to 2009. He is currently a member of PPPL’s Computational Sciences Department. 

“PPPL has a long history of developing models that can analyze and predict the behavior of plasmas in fusion reactions, and our Theory Department and now our Computational Sciences Department have led the way in this effort,” said Jonathan Menard, PPPL’s deputy director for research. “Bill has been a pioneer in this field from the beginning, and I congratulate him for this very well-deserved award.”
 

Using computer science from the beginning

Since the start of his career in the 1970s, Tang has used computers to analyze and predict the behavior of the ionized gas called plasma in fusion reactions. When superfast computers became available, he saw their usefulness in analyzing fusion reactions with the ultimate goal of putting fusion energy on the electrical grid. “When you’re using increasingly powerful computers, this is a vital part of your ‘toolkit,’ and you grow with it to enhance the essential verification, validation and uncertainty quantification capabilities of the modern software,” he said.

In the early 2000s, Tang was one of the founders of the DOE’s Scientific Discovery through Advanced Computing (SCiDAC) program. In 2019, he was a co-author of an influential research paper published in Nature in which the researchers described how they used supercomputers to analyze massive amounts of data from the Joint European Torus, a fusion experiment in the U.K., and the DIII-D National Fusion Facility at General Atomics in San Diego. They used the data to create a model to accurately predict instabilities that can disrupt fusion reactions. Since such dangerous disruptions can cause damage to fusion facilities, finding ways to mitigate them is a key challenge in developing fusion energy as a clean energy source. With the “transfer learning” capability established in the Nature paper, the researchers said the model could be applied to other fusion experiments, such as proposed fusion pilot plants and, eventually, the multinational burning plasma ITER experiment in France. 

“Bill’s pioneering work and experience applying deep learning is helping the Computational Sciences Department open new avenues and lines of research into AI for science,” said Shantenu Jha, head of the Computational Sciences Department.
 

Research on the Aurora Exascale Supercomputer 

Tang and his collaborators are continuing this research on the Aurora Exascale Supercomputer at Argonne National Laboratory. He is part of the Aurora Early Science Program of the Argonne Leadership Computing Facility, a DOE national user facility. Their research aims to develop software that could be used on the control systems of fusion facilities to predict and mitigate disruptions. “You need these innovative surrogate models to give you ‘near-real-time’ first-principles physics guidance,” Tang said. “Modern exascale supercomputers are extremely fast and can achieve these challenging tasks.” 

The Sidney Fernbach Memorial Award is one of several Tang has received for his pioneering work. He was awarded the NVIDIA Corp.’s 2018 Global Impact Award “for groundbreaking work in using graphics processing unit-accelerated computing to unleash deep-learning neural networks for dramatically increasing the accuracy and speed in predicting dangerous disruptions in fusion systems.” The International Data Corporation recognized him with a High Performance Computing (HPC) Innovation Excellence Award in 2013 for “using high-end supercomputing resources to carry out advanced simulations for the first time of confinement physics in large-scale magnetic fusion energy plasmas.” In 2005, he received the Distinguished Achievement Award from the Chinese Institute of Engineers-USA for “outstanding leadership in fusion research and contributions to fundamentals of plasma science.”

Tang has served on the International Scientific Advisory Committee for the Swiss National Supercomputing Centre for more than a decade and is the current chairman of the organization’s Platform for Advanced Scientific Computing’s advisory board. He is the author of more than 200 peer-reviewed publications with more than 17,000 Google Scholar citations and has been a fellow of the American Physical Society since 1978. 

Tang and his wife, Song Kim Tang, live in Princeton, New Jersey, and have a grown daughter, Andrea Tang, a successful novelist who lives in Washington, DC.