Zhangyang “Atlas” Wang
Also known as Atlas Wang, Zhangyang Wang
Zhangyang “Atlas” Wang studies efficient training and deployment of generative models for language and vision. He completed a B.E. in EEIS at USTC in 2012 and a Ph.D. in ECE at UIUC in 2016, advised by Thomas Huang, then joined Texas A&M in 2017 and The University of Texas at Austin in 2020. In 2022 he received an NSF CAREER award and IEEE Intelligent Systems named him one of AI's 10 to Watch; GaLore, which he coauthored, appeared at ICML in 2024 on memory-efficient training of large language models. He received the 2026 IAPR Aggarwal Prize for contributions to the efficient training and deployment of generative models, with applications to language and vision. He is research director at XTX Markets in New York City, on leave since May 2024 from an associate professorship at The University of Texas at Austin.
- Now at
- University of Texas at Austin and XTX Markets
- Works
- 470
- Citations
- 21,258
- h-index
- 61
Publication numbers from OpenAlex, as of 17 October 2026.
Timeline
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2012–2016
Degrees at USTC and UIUC
He earns a B.E. in EEIS from USTC in 2012 and a Ph.D. in ECE from UIUC in 2016, advised by Thomas S. Huang.
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2017–2020
Assistant professor at Texas A&M
He serves as an assistant professor of computer science and engineering at Texas A&M University from 2017 to 2020.
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2020–2023
Kilby professor at UT Austin
He is the Jack Kilby/Texas Instruments Endowed Assistant Professor in electrical and computer engineering at The University of Texas at Austin from 2020 to 2023.
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2021–2024
Amazon Search and Picsart
He is a visiting scholar at Amazon Search from 2021 to 2022, applying geometric deep learning to recommendation systems. From 2022 to 2024 he is part-time director of AI research and technology at Picsart, where he runs the company's video generative AI work.
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2022
CAREER and AI's 10 to Watch
In 2022 he receives an NSF CAREER award for learning optimization algorithms from data, on interpretability, reliability, and scalability. IEEE Intelligent Systems names him one of the 2022 AI's 10 to Watch for efficient and reliable machine learning.
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2024
GaLore for LLM training
In 2024, Zhangyang Wang and coauthors present GaLore at ICML, on memory-efficient training of large language models by gradient low-rank projection.
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2026
The Aggarwal Prize
He receives the 2026 J. K. Aggarwal Prize from the International Association for Pattern Recognition for contributions to the efficient training and deployment of generative models, with applications to language and vision.
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Since May 2024
Research director at XTX Markets
Since May 2024, he serves as full-time research director for XTX Markets in New York City, on leave from an associate professorship at The University of Texas at Austin. He founds and leads the firm's AI lab in New York City.
Sources and credits
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- Atlas Wang | Texas ECE - Electrical & Computer Engineering at UT Austin
- Atlas Wang
- Five Texas ECE Faculty Receive NSF CAREER Awards | Texas ECE - Electrical & Computer Engineering at UT Austin
- 2022 AI's 10 to Watch Announced | IEEE Computer Society
- [2403.03507] GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
- Atlas Wang – DeepLearn 2025
- J. K. Aggarwal Prize – International Association for Pattern Recognition
- Atlas Wang Wins 2026 J.K. Aggarwal Prize from IAPR | Texas ECE - Electrical & Computer Engineering at UT Austin
- Zhangyangwang | ICPR2026website
- Atlas Wang – ICTERI