Efficient AI Computing,
Transforming the Future.

Wei-Chen Wang

Postdoctoral

(Graduated)

His research focuses on efficient deep learning, TinyML, embedded systems, and memory/storage systems. Wei-Chen has received several accolades for his work, including the MLSys Best Paper Award, the Best Poster Award at the NSF Athena AI Institute, the ACM/IEEE CODES+ISSS Best Paper Award, and the IEEE NVMSA Best Paper Award. In addition, he received first place (among 150 teams) in the flash consumption track of the ACM/IEEE TinyML Design Contest at ICCAD 2022. His research has received over 4,000 stars on GitHub, and his work "On-device training under 256KB memory" (MCUNetV3) was highlighted by the MIT homepage. He will join Amazon as an Applied Scientist.

Honors and Fellowships

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Competition Awards

First Place (1/150)
,
ACM/IEEE TinyML Design Contest
,
Memory Occupation Track
, @
ICCAD
,
2022
HAT

Awards

Wei-Chen Wang
team
received
2023 NSF Athena AI Institute Best Poster Award
of
.

Open source projects with over 1K GitHub stars

Projects

Blog Posts

Talks

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