• IEEE.org
  • IEEE CS Standards
  • Career Center
  • About Us
  • Subscribe to Newsletter

0

IEEE
CS Logo
  • MEMBERSHIP
  • CONFERENCES
  • PUBLICATIONS
  • EDUCATION & CAREER
  • VOLUNTEER
  • ABOUT
  • Join Us
CS Logo

0

IEEE Computer Society Logo
Sign up for our newsletter
IEEE COMPUTER SOCIETY
About UsBoard of GovernorsNewslettersPress RoomIEEE Support CenterContact Us
COMPUTING RESOURCES
Career CenterCourses & CertificationsWebinarsPodcastsTech NewsMembership
BUSINESS SOLUTIONS
Corporate PartnershipsConference Sponsorships & ExhibitsAdvertisingRecruitingDigital Library Institutional Subscriptions
DIGITAL LIBRARY
MagazinesJournalsConference ProceedingsVideo LibraryLibrarian Resources
COMMUNITY RESOURCES
GovernanceConference OrganizersAuthorsChaptersCommunities
POLICIES
PrivacyAccessibility StatementIEEE Nondiscrimination PolicyIEEE Ethics ReportingXML Sitemap

Copyright 2025 IEEE - All rights reserved. A public charity, IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity.

  • Home
  • /Profiles
  • Home
  • /Profiles

William M. Tang

Award Recipient

Featured ImageFeatured Image

Prof. William M. (Bill) Tang of Princeton University is a Lecturer with the Rank of Professor in the Department of Astrophysical Sciences at Princeton University. He is also a Participating Faculty at the Center for Statistics and Machine Learning, an Executive Committee member for the Princeton Institute for Computational Science & Engineering (PICSciE), and a Principal Research Physicist at the Princeton Plasma Physics Laboratory, the DOE National Laboratory for Plasma Physics and Fusion Energy Research -- where he served as Chief Scientist from 1997 to 2009. A Fellow of the American Physical Society, he has received awards, including NVIDIA Corporation’s 2018 Global Impact Award “for groundbreaking work in using GPU-accelerated computing to unleash deep learning neural networks for dramatically increasing the accuracy and speed in predicting dangerous disruptions in fusion systems,” and the IEEE Computer Society’s 2024 Sidney Fernbach Memorial Award – “for pioneering contributions to fusion energy research accelerated by high-performance computing and deep learning.”

He was also previously honored with the Distinguished Achievement Award (2006) for “outstanding leadership in fusion research and contributions to fundamentals of plasma science” by the Chinese Institute of Engineers-USA. His scientific leadership roles have included serving on the International Scientific Advisory Committee for Switzerland’s National Supercomputing Center (CSCS) and as the current Chairman for their “PASC” Scientific Advisory Board. He is also the PI (principal investigator) for projects, including the “Accelerated Deep Learning Discovery in Fusion Energy Science” Early Science Project at the Argonne National Laboratory on their current Exascale system, AURORA. He was also the PI for the Intel Parallel Computing Center of Excellence, which was awarded to “PICSciE” at Princeton University (2014-2018). Professor Tang has been the author of more than 200 peer-reviewed journal publications with over 17,000 Google Scholar citations, and his PhD students include recipients of the US Presidential Early Career Award for Scientists and Engineers in 2000 and 20005.

Awards

2024 Sidney Fernbach Memorial Award
“For pioneering contributions in fusion energy research accelerated by high-performance computing and deep learning.”
Learn more about the Sidney Fernbach Memorial Award

LATEST NEWS
IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT
IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT
Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)
Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)
Autonomous Observability: AI Agents That Debug AI
Autonomous Observability: AI Agents That Debug AI
Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference
Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference
Copilot Ergonomics: UI Patterns that Reduce Cognitive Load
Copilot Ergonomics: UI Patterns that Reduce Cognitive Load
Read Next

IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT

Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)

Autonomous Observability: AI Agents That Debug AI

Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference

Copilot Ergonomics: UI Patterns that Reduce Cognitive Load

The Myth of AI Neutrality in Search Algorithms

Gen AI and LLMs: Rebuilding Trust in a Synthetic Information Age

How AI Is Transforming Fraud Detection in Financial Transactions

FacebookTwitterLinkedInInstagramYoutube
Get the latest news and technology trends for computing professionals with ComputingEdge
Sign up for our newsletter