The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Song Han sits on this spectrum.
This scientist: 119 publications — 14th percentile
14% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Song Han sits on this spectrum.
This scientist: 54 D-Index — 69th percentile
69% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Song Han is affiliated with MIT in the United States and has made contributions primarily in the fields of computer science and engineering. Their research focuses on areas including computer vision and pattern recognition, artificial intelligence, electrical and electronic engineering, aerospace engineering, and computer networks and communications.
The scientist's work encompasses multiple topics, such as advanced neural network applications, quantum computing algorithms and architecture, quantum information and cryptography, human pose and action recognition, adversarial robustness in machine learning, video surveillance and tracking methods, and domain adaptation and few-shot learning.
Song Han has published extensively, with a notable presence in venues such as arXiv (Cornell University), IEEE Transactions on Pattern Analysis and Machine Intelligence, Applied Intelligence, Proceedings of the 59th ACM/IEEE Design Automation Conference, and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.
Frequent coauthors of Song Han include Zhijian Liu, Ji Lin, Hanrui Wang, Yujun Lin, and Jiaqi Gu.
The range of Song Han's research venues and collaboration networks reflects involvement in diverse topics primarily related to neural networks, hardware acceleration, and deep learning on resource-constrained devices.
Song Han;Huizi Mao;William J. Dally;William J. Dally
Forrest N. Iandola;Song Han;Matthew W. Moskewicz;Khalid Ashraf
Song Han;Jeff Pool;John Tran;William J. Dally
Song Han;Xingyu Liu;Huizi Mao;Jing Pu
Ji Lin;Chuang Gan;Song Han
Han Cai;Ligeng Zhu;Song Han
Yihui He;Ji Lin;Zhijian Liu;Hanrui Wang
Ligeng Zhu;Zhijian Liu;Song Han
Yujun Lin;Song Han;Huizi Mao;Yu Wang
Kuan Wang;Zhijian Liu;Yujun Lin;Ji Lin
Chenzhuo Zhu;Song Han;Huizi Mao;William J. Dally
Lei Deng;Guoqi Li;Song Han;Luping Shi
Han Cai;Chuang Gan;Tianzhe Wang;Zhekai Zhang
Song Han;Junlong Kang;Huizi Mao;Yiming Hu
Haotian Tang;Zhijian Liu;Shengyu Zhao;Shengyu Zhao;Yujun Lin
Kaiyuan Guo;Lingzhi Sui;Jiantao Qiu;Jincheng Yu
Javier Duarte;Edward Kreinar;Maurizio Pierini;Nhan Tran
Zhijian Liu;Haotian Tang;Yujun Lin;Song Han
Shengyu Zhao;Zhijian Liu;Ji Lin;Jun-Yan Zhu
Javier Duarte;Song Han;Philip Harris;Sergo Jindariani
Ji Lin;Wei-Ming Chen;Yujun Lin;john cohn
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