Vivienne Sze
Vivienne Sze designs low-power circuits and energy-aware algorithms for machine learning, computer vision, and video coding. She completed electrical engineering degrees at the University of Toronto in 2004 and at MIT in 2006 and 2010, then spent September 2010 to July 2013 at Texas Instruments on High Efficiency Video Coding and shared in the standard's 2017 Primetime Engineering Emmy Award as a member of the Joint Collaborative Team on Video Coding. With Yu-Hsin Chen, Tushar Krishna, and Joel Emer, she presented Eyeriss in February 2016, a convolutional-neural-network chip 10 times as efficient as a mobile GPU. In 2020 she coauthored Efficient Processing of Deep Neural Networks with Yu-Hsin Chen, Tien-Ju Yang, and Joel Emer and became the inaugural winner of the ACM-W Rising Star Award. She joined the MIT faculty in 2013 and is a full professor of electrical engineering and computer science, effective in July 2024, and in June 2026 she was an author of Gleanmer, a chip for real-time 3D mapping.
- Works
- 177
- Citations
- 17,241
- h-index
- 41
Publication numbers from OpenAlex, as of 17 October 2026.
Timeline
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2004–2010
Degrees at Toronto and MIT
She completes a B.A.Sc. (Hons) in electrical engineering at the University of Toronto in 2004, then an S.M. in 2006 and a Ph.D. in 2010, both in electrical engineering at MIT. In 2011 she receives MIT's Jin-Au Kong Outstanding Doctoral Thesis Prize in electrical engineering.
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September 2010–July 2013
Video coding at Texas Instruments
From September 2010 to July 2013 she is a Member of Technical Staff in the Systems and Applications R&D Center at Texas Instruments in Dallas, where she designs low-power algorithms and architectures for video coding. She represents TI on the Joint Collaborative Team on Video Coding during the development of High Efficiency Video Coding.
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2013
Assistant professor at MIT
She joins MIT in 2013 as an assistant professor of electrical engineering and computer science.
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February 2016
The Eyeriss accelerator
In February 2016 she, Yu-Hsin Chen, Tushar Krishna, and Joel Emer present Eyeriss at the International Solid-State Circuits Conference. The chip implements convolutional neural networks and is 10 times as efficient as a mobile GPU.
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2017
A Primetime Engineering Emmy
In 2017, as a member of the Joint Collaborative Team on Video Coding, she receives a Primetime Engineering Emmy Award for the HEVC video compression standard.
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2020
A book and ACM-W award
With Yu-Hsin Chen, Tien-Ju Yang, and Joel S. Emer, she coauthors Efficient Processing of Deep Neural Networks, published by Morgan & Claypool in 2020. In 2020 she becomes the inaugural winner of the ACM-W Rising Star Award.
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July 2024
Full professor at MIT
MIT promotes her to full professor of electrical engineering and computer science, effective in July 2024. Her research involves the co-design of energy-aware signal processing algorithms and low-power circuits for machine learning, computer vision, and video coding.
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June 2026
A chip called Gleanmer
In June 2026 she is an author of "Gleanmer: A 6 mW SoC for Real-Time 3D Gaussian Occupancy Mapping," with Zih-Sing Fu and Sertac Karaman.
Sources and credits
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- Energy-Efficient Multimedia Systems Group - Principal Investigator: Vivienne Sze
- Vivienne Sze - RLE at MIT
- ACM-W Rising Star Award Recipient: Vivienne Sze
- Department of EECS Announces 2024 Promotions - MIT EECS
- New Core Faculty Profile: Vivienne Sze
- Eyeriss Project
- Energy-friendly chip can perform powerful artificial-intelligence tasks
- Vivienne Sze - Wikipedia
- New chip could help tiny robots traverse complex environments
- Energy-Efficient Multimedia Systems Group - Awards