基本信息
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Bio
His research focuses on efficient deep learning computing. He proposed “deep compression” technique that can reduce neural network size by an order of magnitude without losing accuracy, and the hardware implementation “efficient inference engine” that first exploited pruning and weight sparsity in deep learning accelerators. His team’s work on hardware-aware neural architecture search (ProxylessNAS, Once-for-All Network (OFA), MCUNet) was integrated in Facebook, Amazon, Microsoft, Intel, SONY, received the first place in six low-power computer vision contest awards in flagship AI conferences. Song received Best Paper awards at ICLR and FPGA, multiple faculty awards from Amazon, SONY, Facebook, NVIDIA and Samsung. Song was named “35 Innovators Under 35” by MIT Technology Review for his contribution on “deep compression” technique that “lets powerful artificial intelligence (AI) programs run more efficiently on low-power mobile devices.” Song received the NSF CAREER Award for “efficient algorithms and hardware for accelerated machine learning” and the IEEE “AIs 10 to Watch: The Future of AI” award.
Research Interests
Papers共 206 篇Author StatisticsCo-AuthorSimilar Experts
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CoRR (2025)
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arxiv(2025)
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Dacheng Li, Yunhao Fang,Yukang Chen, Shuo Yang, Shiyi Cao,Justin Wong,Michael Luo,Xiaolong Wang,Hongxu Yin,Joseph E. Gonzalez,Ion Stoica,Song Han,Yao Lu
CoRR (2025)
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arxiv(2025)
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Haotian Tang, Yecheng Wu,Shang Yang,Enze Xie,Junsong Chen, Junyu Chen,Zhuoyang Zhang,Han Cai,Yao Lu,Song Han
ICRA 2025 (2025)
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arxiv(2025)
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Chaofan Lin, Jiaming Tang, Shuo Yang, Hanshuo Wang, Tian Tang,Boyu Tian,Ion Stoica,Song Han,Mingyu Gao
CoRR (2025)
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Haocheng Xi, Shuo Yang, Yilong Zhao,Chenfeng Xu,Muyang Li,Xiuyu Li,Yujun Lin,Han Cai, Jintao Zhang,Dacheng Li,Jianfei Chen,Ion Stoica,Kurt Keutzer,Song Han
CoRR (2025)
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CoRR (2025)
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Author Statistics
#Papers: 206
#Citation: 66851
H-Index: 60
G-Index: 143
Sociability: 6
Diversity: 2
Activity: 191
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